CN113076301B

Movatterモバイル変換

Info

Publication number: CN113076301B
Application number: CN202110352335.XA
Authority: CN
Inventors: 赵航
Original assignee: Beijing Sogou Technology Development Co Ltd
Current assignee: Beijing Sogou Technology Development Co Ltd
Priority date: 2021-03-31
Filing date: 2021-03-31
Publication date: 2025-02-07
Anticipated expiration: 2041-03-31
Also published as: CN113076301A

Abstract

The application discloses a method for constructing a knowledge base, an information query method, an information query device and equipment, wherein the knowledge base of a medicine is firstly constructed through medicine entity records; and finally, determining the association relation between the drug entity and the non-drug domain entity in the related knowledge base based on the drug entity information corresponding to the drug entity in the drug knowledge base, and generating the query knowledge base based on the drug knowledge base, the related knowledge base and the association relation between the drug entity and the non-drug domain entity. By acquiring the query request for the drug information sent by the client, the corresponding entity and query intention can be identified from the query request, and the query is performed in the query knowledge base according to the identified entity and query intention, so as to obtain a query result. The quick inquiry can be realized through the established inquiry knowledge base, and accurate and comprehensive medicine information meeting the needs of users is obtained.

Description

Knowledge base construction method, information query method, device and equipment

Technical Field

The application relates to the technical field of internet, in particular to a method for constructing a knowledge base, an information query method, an information query device and information query equipment.

Background

When a patient purchases a drug or takes a drug, the patient needs to acquire drug information related to disease symptoms and his own physical condition.

At present, the process of acquiring the medicine information is complex, and the patient is inconvenient to acquire the related medicine information. Moreover, the obtained drug information may not be complete and accurate enough to meet the needs of the patient to select or use the drug. Therefore, how to obtain complete and accurate medicine information more conveniently becomes a problem to be solved.

Disclosure of Invention

In view of this, embodiments of the present application provide a method, an information query method, an apparatus, and a device for constructing a knowledge base, which can build a query knowledge base of drug information, and provide a relatively complete and accurate query result based on the query knowledge base, so as to facilitate a user to query drug information.

In order to solve the above problems, the technical solution provided by the embodiment of the present application is as follows:

A method of building a knowledge base, the method comprising:

Acquiring a medicine entity record, wherein the medicine entity record comprises a medicine entity and medicine entity information of the medicine entity, and the medicine entity information comprises at least one medicine information field and medicine information corresponding to the medicine information field;

Establishing a medicine knowledge base based on the medicine entity, the medicine entity record corresponding to the medicine entity and the association relation between the medicine entity and the medicine entity record;

determining a related knowledge base associated with the medicine knowledge base according to a medicine information history query record, wherein the related knowledge base comprises non-medicine domain entities which are associated with the medicine entities;

According to the medicine entity information of the medicine entity, establishing an association relationship between the medicine entity and the non-medicine domain entity in the related knowledge base;

And generating a query knowledge base of medicine information based on the medicine knowledge base, a related knowledge base related to the medicine knowledge base and the association relation between medicine entities in the medicine knowledge base and non-medicine domain entities in the related knowledge base.

In one possible implementation manner, the establishing a drug knowledge base based on the drug entity, the drug entity record corresponding to the drug entity, and the association relationship between the drug entity and the drug entity record, includes:

Determining the association relation between the medicine entities according to medicine information corresponding to the tabu information field and/or the notice information field in the medicine entity information and medicine information corresponding to the medicine component type field;

And adding the medicine entity records to a medicine knowledge base, and associating the medicine entities with association relations aiming at the medicine entities corresponding to the medicine entity records in the medicine knowledge base.

In a possible implementation manner, the determining the association relationship between the drug entities according to the drug information corresponding to the tabu information field and/or the notice field in the drug entity information and the drug information corresponding to the drug component type field includes:

Reading a tabu information field and/or a notice field in medicine entity information of a first medicine entity to obtain the tabu information and/or the notice of the first medicine entity;

Identifying information related to medicine components and association relations from the tabu information and/or notice information of the first medicine entity, determining the identified information related to the medicine components as a target medicine component type, and determining the identified information related to the association relations as a target association relation type;

and acquiring a medicine entity of which the medicine component type belongs to the target medicine component type from the medicine knowledge base, constructing an association relationship between the medicine entity and the first medicine entity, and setting the association relationship type as the target association relationship type.

In one possible implementation manner, the determining a relevant knowledge base associated with the drug knowledge base according to the drug information history query record includes:

performing entity identification on the medicine information history inquiry records to obtain non-medicine field entities and types of the entities included in the medicine information history inquiry records;

And determining a related knowledge base associated with the medicine knowledge base according to the type of the entity.

In one possible implementation, the relevant knowledge base includes a symptom knowledge base, a crowd knowledge base, a food material knowledge base, and a sports knowledge base;

The establishing the association relationship between the drug entity and the non-drug domain entity in the relevant knowledge base according to the drug entity information of the drug entity comprises the following steps:

And establishing association relations between the medicine entity and the symptom entity in the symptom knowledge base, between the crowd entity in the crowd knowledge base, between the food material entity in the food material knowledge base and between the medicine entity and the sport entity in the sport knowledge base according to the medicine entity information of the medicine entity.

In one possible implementation, the method comprises the steps of reading information corresponding to an indication field in drug entity information of a second drug entity to obtain indication of the second drug entity;

And acquiring a symptom entity corresponding to the indication of the second medicine entity from the symptom knowledge base, and constructing an association relationship between the symptom entity and the second medicine entity.

In one possible implementation, the method includes:

Reading information corresponding to a tabu information field and/or a notice field in drug entity information of a second drug entity to obtain the tabu information and/or the notice of the second drug entity;

Identifying information related to the applicable group of people from the contraindication information and/or the notice information of the second drug entity;

and acquiring crowd entities corresponding to the information related to the applicable crowd in the crowd knowledge base, and constructing an association relationship between the crowd entities and the second medicine entity.

In one possible implementation, the method includes:

Identifying information related to food material from the tabu information and/or the notice information of the second drug entity;

And acquiring food material entities corresponding to the information related to the food materials in the food material knowledge base, and constructing the association relationship between the food material entities and the second medicine entities.

In one possible implementation, the method includes:

Identifying movement related information from the contraindications information and/or the notice information of the second pharmaceutical entity;

and acquiring a motion entity corresponding to the motion related information in the motion knowledge base, and constructing an association relationship between the motion entity and the second medicine entity.

An information query method, the method comprising:

Acquiring a query request of medicine information sent by a client;

Identifying at least one of a drug entity or a non-drug domain entity from the query request;

Determining a query intention according to the query request;

Inquiring an inquiry knowledge base according to the inquiry intention and at least one of the obtained medicine entity or the non-medicine domain entity to obtain an inquiry result, wherein the inquiry knowledge base is constructed according to the method for constructing the knowledge base;

And sending the query result to the client.

In one possible implementation manner, before querying the query knowledge base according to the query intention and at least one of the obtained drug entity or the non-drug domain entity, the method further includes:

Acquiring user figure information;

and obtaining the corresponding non-medicine field entity according to the user character image information.

In one possible implementation manner, the querying the query knowledge base according to the query intention and at least one of the obtained drug entity or the non-drug domain entity to obtain a query result includes:

When inquiring the inquiring knowledge base according to the medicine entity, determining a medicine information field to be inquired corresponding to the medicine entity according to the inquiring intention;

and acquiring medicine information corresponding to the medicine information field to be queried based on a medicine knowledge base included in the query knowledge base, and obtaining a query result.

In one possible implementation, the method further includes:

Acquiring non-drug domain entities associated with the drug entities according to the query intention based on the association relationship between the drug entities in the drug knowledge base and the non-drug domain entities in the related knowledge base;

and acquiring entity information corresponding to the non-drug field entity associated with the drug entity based on the related knowledge base included in the query knowledge base, and adding the entity information into the query result.

When a query knowledge base is queried according to non-medicine domain entities, acquiring medicine entities associated with the non-medicine domain entities based on association relations between medicine entities in the medicine knowledge base and the non-medicine domain entities in the related knowledge base, wherein the association relations are included in the query knowledge base;

determining a medicine information field to be queried corresponding to the medicine entity according to the query intention;

In one possible implementation, the method further includes:

And acquiring entity information corresponding to the non-drug domain entity based on a related knowledge base included in the query knowledge base, and adding the entity information into the query result.

An apparatus for building a knowledge base, the apparatus comprising:

A first obtaining unit, configured to obtain a drug entity record, where the drug entity record includes a drug entity and drug entity information of the drug entity, and the drug entity information includes at least one drug information field and drug information corresponding to the drug information field;

the first establishing unit is used for establishing a medicine knowledge base based on the medicine entity, the medicine entity record corresponding to the medicine entity and the association relation between the medicine entity and the medicine entity record;

A first determining unit, configured to determine a relevant knowledge base associated with the drug knowledge base according to a drug information history query record, where the relevant knowledge base includes non-drug domain entities associated with the drug entity;

a second establishing unit, configured to establish an association relationship between the drug entity and a non-drug domain entity in the relevant knowledge base according to drug entity information of the drug entity;

and the generation unit is used for generating a query knowledge base of the medicine information based on the medicine knowledge base, a related knowledge base related to the medicine knowledge base and the association relation between the medicine entities in the medicine knowledge base and the non-medicine domain entities in the related knowledge base.

In one possible implementation manner, the first establishing unit includes:

a first determining subunit, configured to determine an association relationship between the drug entities according to drug information corresponding to a tabu information field and/or a notice field in the drug entity information and drug information corresponding to a drug component type field;

and the association subunit is used for adding the drug entity records to a drug knowledge base and associating the drug entities with association relations aiming at the drug entities corresponding to the drug entity records in the drug knowledge base.

In one possible implementation manner, the first determining subunit includes:

the first reading subunit is used for reading the tabu information field and/or the notice field in the medicine entity information of the first medicine entity to obtain the tabu information and/or the notice of the first medicine entity;

A second determination subunit, configured to identify information related to a drug component and an association relationship from tabu information and/or notice information of the first drug entity, determine the identified information related to the drug component as a target drug component type, and determine the identified information related to the association relationship as a target association relationship type;

The construction subunit is configured to obtain a drug entity whose drug component type belongs to the target drug component type from the drug knowledge base, construct an association relationship between the drug entity and the first drug entity, and set the association relationship type as the target association relationship type.

In a possible implementation manner, the first determining unit is specifically configured to identify an entity in the drug information history query record, so as to obtain a non-drug domain entity and a type to which the entity belongs, where the non-drug domain entity is included in the drug information history query record;

The generation unit is specifically configured to establish, according to the drug entity information of the drug entity, an association relationship between the drug entity and the symptom entity in the symptom knowledge base, the crowd entity in the crowd knowledge base, the food entity in the food knowledge base, and the sports entity in the sports knowledge base.

In one possible implementation manner, the generating unit includes:

The system comprises a first reading subunit, a second reading subunit, a first judging subunit, a second judging subunit, a first judging subunit and a second judging subunit, wherein the first reading subunit is used for reading information corresponding to an indication field in medicine entity information of a second medicine entity to obtain the indication of the second medicine entity;

the first construction subunit is configured to acquire a symptom entity corresponding to the indication of the second drug entity from the symptom knowledge base, and construct an association relationship between the symptom entity and the second drug entity.

In one possible implementation manner, the generating unit includes:

the second reading subunit is used for reading information corresponding to the tabu information field and/or the notice field in the medicine entity information of the second medicine entity to obtain the tabu information and/or the notice of the second medicine entity;

A first identifying subunit, configured to identify information related to the applicable group from the tabu information and/or the notice information of the second drug entity;

The second construction subunit is configured to obtain crowd entities corresponding to the information related to the applicable crowd in the crowd knowledge base, and construct an association relationship between the crowd entities and the second drug entity.

In one possible implementation manner, the generating unit includes:

A third reading subunit, configured to read information corresponding to a tabu information field and/or a notice field in drug entity information of a second drug entity, to obtain tabu information and/or notice of the second drug entity;

A second identifying subunit for identifying information related to food material from the tabu information and/or the notice information of the second drug entity;

And the third construction subunit is used for acquiring food material entities corresponding to the information related to the food materials in the food material knowledge base and constructing the association relationship between the food material entities and the second medicine entities.

In one possible implementation manner, the generating unit includes:

A fourth reading subunit, configured to read information corresponding to a tabu information field and/or a notice field in drug entity information of a second drug entity, to obtain tabu information and/or notice of the second drug entity;

a third identifying subunit for identifying information related to movement from the tabu information and/or the notice information of the second drug entity;

and a fourth construction subunit, configured to acquire a motion entity corresponding to the motion-related information in the motion knowledge base, and construct an association relationship between the motion entity and the second drug entity.

An information query apparatus, the apparatus comprising:

The second acquisition unit is used for acquiring a query request of the medicine information sent by the client;

The identification unit is used for identifying and obtaining at least one of a medicine entity or a non-medicine domain entity from the query request;

A second determining unit, configured to determine a query intention according to the query request;

The query unit is used for querying a query knowledge base according to the query intention and at least one of the obtained medicine entity or the non-medicine domain entity to obtain a query result, wherein the query knowledge base is constructed according to the device for constructing the knowledge base;

and the sending unit is used for sending the query result to the client.

In one possible implementation, the apparatus further includes:

a third acquisition unit for acquiring the portrait information of the user;

And the fourth acquisition unit is used for acquiring the corresponding non-medicine field entity according to the user character image information.

In one possible implementation, the query unit includes:

A third determining subunit, configured to determine, according to the query intention, a drug information field to be queried corresponding to a drug entity when querying a query knowledge base according to the drug entity;

The first obtaining subunit is configured to obtain, based on a drug knowledge base included in the query knowledge base, drug information corresponding to the drug information field to be queried, and obtain a query result.

In one possible implementation, the apparatus further includes:

The second obtaining subunit is configured to obtain, according to the query intention, a non-drug domain entity associated with the drug entity based on an association relationship between the drug entity in the drug knowledge base and the non-drug domain entity in the relevant knowledge base, where the association relationship is included in the query knowledge base;

And the third acquisition subunit is used for acquiring entity information corresponding to the non-drug field entity associated with the drug entity based on the related knowledge base included in the query knowledge base, and adding the entity information into the query result.

In one possible implementation, the query unit includes:

A fourth obtaining subunit, configured to obtain, when a query knowledge base is queried according to a non-pharmaceutical domain entity, a pharmaceutical entity associated with the non-pharmaceutical domain entity based on an association relationship between a pharmaceutical entity in the pharmaceutical knowledge base and a non-pharmaceutical domain entity in the relevant knowledge base included in the query knowledge base;

a fourth determining subunit, configured to determine, according to the query intention, a drug information field to be queried corresponding to the drug entity;

and a fifth obtaining subunit, configured to obtain, based on the drug knowledge base included in the query knowledge base, drug information corresponding to the drug information field to be queried, and obtain a query result.

In one possible implementation, the apparatus further includes:

and a sixth obtaining subunit, configured to obtain entity information corresponding to the entity in the non-pharmaceutical field based on the relevant knowledge base included in the query knowledge base, and add the entity information to the query result.

An apparatus for building a knowledge base, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs comprising instructions for:

In one possible implementation, the processor is specifically further configured to execute the one or more programs to include instructions for:

Reading information corresponding to an indication field in drug entity information of a second drug entity to obtain the indication of the second drug entity;

An apparatus for information querying, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs comprising instructions for:

Acquiring a query request of medicine information sent by a client;

Determining a query intention according to the query request;

inquiring an inquiry knowledge base according to the inquiry intention and at least one of the obtained medicine entity or the non-medicine domain entity to obtain an inquiry result, wherein the inquiry knowledge base is constructed according to the equipment for constructing the knowledge base;

And sending the query result to the client.

Acquiring user figure information;

A computer readable medium having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform the method of building a knowledge base described above, or to perform the information query method described above.

From this, the embodiment of the application has the following beneficial effects:

the method, the information query device and the equipment for constructing the knowledge base are provided by the embodiment of the application, the medicine knowledge base is firstly established through the medicine entity record, then the related knowledge base related to the medicine knowledge base is determined according to the medicine information history query record, and finally the association relationship between the medicine entity in the medicine knowledge base and the non-medicine domain entity in the related knowledge base is determined based on the medicine entity information corresponding to the medicine entity in the medicine knowledge base. And generating a query knowledge base of the medicine information by using the medicine knowledge base, the related knowledge base and the association relation between the medicine entity and the non-medicine domain entity in the related knowledge base. Based on the query knowledge base, more accurate and complete query of medicine information can be performed. By acquiring the query request for the drug information sent by the client, the corresponding entity and query intention can be identified from the query request, and the query is performed in the query knowledge base according to the identified entity and query intention, so as to obtain a query result. The quick inquiry of the medicine information can be realized through the established inquiry knowledge base, and the accurate and comprehensive medicine information meeting the needs of users can be obtained.

Drawings

Fig. 1 is a schematic diagram of an exemplary application scenario of an information query method according to an embodiment of the present application;

FIG. 2 is a flowchart of a method for constructing a knowledge base according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a structure of a query knowledge base according to an embodiment of the present application;

FIG. 4 is a flowchart of an information query method according to an embodiment of the present application;

FIG. 5 is a schematic structural diagram of an apparatus for building a knowledge base according to an embodiment of the present application;

Fig. 6 is a schematic structural diagram of an information query apparatus according to an embodiment of the present application;

FIG. 7 is a schematic structural diagram of an apparatus for building a knowledge base according to an embodiment of the present application;

Fig. 8 is a schematic structural diagram of an information query apparatus according to an embodiment of the present application;

Fig. 9 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

In order that the above-recited objects, features and advantages of the present application will become more readily apparent, a more particular description of embodiments of the application will be rendered by reference to the appended drawings and appended drawings.

In order to facilitate understanding of the technical solution provided by the present application, the following description will first explain the background art of the present application.

The inventor finds that for common lighter diseases, patients may consider selecting medicines by themselves after researching traditional medicine information acquisition methods, and for medicines prescribed by doctors, patients may need to know about taking relevant notes of the medicines before using the medicines. The user has a need to obtain the drug information, and the user can generally query, read the instruction book of the drug or ask a professional doctor or pharmacist to obtain the drug information through the network. However, the medicine information acquired by the user through the method may not be accurate and comprehensive enough and may not be consistent with the required medicine information.

Based on the above, the embodiment of the application provides a method, an information query method, a device and equipment for constructing a knowledge base, wherein a medicine knowledge base is firstly established through medicine entity records, then a relevant knowledge base related to the medicine knowledge base can be determined according to medicine information history query records, and finally, the association relationship between medicine entities in the medicine knowledge base and non-medicine domain entities in the relevant knowledge base is determined based on medicine entity information corresponding to medicine entities in the medicine knowledge base. And generating a query knowledge base of the medicine information by using the medicine knowledge base, the related knowledge base and the association relation between the medicine entity and the non-medicine domain entity in the related knowledge base.

The query knowledge base comprises a medicine knowledge base, a related knowledge base related to the medicine knowledge base and an association relation between medicine entities in the medicine knowledge base and non-medicine domain entities in the related knowledge base. Based on the query knowledge base, more accurate and complete query of medicine information can be performed. By acquiring the query request for the drug information sent by the client, the corresponding entity and query intention can be identified from the query request, and the query is performed in the query knowledge base according to the identified entity and query intention, so as to obtain a query result. The quick inquiry of the medicine information can be realized through the established inquiry knowledge base, and the accurate medicine information meeting the needs of users is obtained.

In order to facilitate understanding of the knowledge base construction method and the information query method provided by the embodiments of the present application, an application scenario of the information query method provided by the embodiments of the present application is described below with reference to fig. 1. Fig. 1 is a schematic diagram of an exemplary application scenario of an information query method according to an embodiment of the present application. The information query method provided by the embodiment of the application can be applied to the server 20.

In practical application, a drug entity record corresponding to a drug entity may be first constructed, where the drug entity record includes a drug entity and drug entity information corresponding to the drug entity. And establishing a medicine knowledge base based on the medicine entity, the corresponding medicine entity record and the association relation between the medicine entity and the corresponding medicine entity record.

In addition, the user may also query for other factors related to the drug, such as crowd, symptoms, food, sports, etc., when querying the drug. Correspondingly, a relevant knowledge base associated with the drug knowledge base may be determined from the historical query record for the drug information. The relevant knowledge base may include non-pharmaceutical domain entities (hereinafter referred to simply as relevant entities) associated with pharmaceutical entities, and entity information corresponding to each entity. The association between the drug entity in the drug knowledge base and the non-drug domain entity in the related knowledge base is established, and the query knowledge base 30 of the drug information can be generated by using the association between the drug knowledge base, the related knowledge base, and the drug entity and the non-drug domain entity in the related knowledge base.

The query knowledge base 30 includes a drug knowledge base, a related knowledge base associated with the drug knowledge base, and an association relationship between drug entities in the drug knowledge base and non-drug domain entities in the related knowledge base, and the query of drug information can be performed by querying the knowledge base 30. If a user needs to query a certain drug information, a query request of the drug information can be sent through the client 10, after the query request is obtained, the server 20 identifies and obtains at least one entity, determines the query intention, and queries in the query knowledge base 30 according to the query intention and the obtained entity to obtain a query result. The query result is sent to the client 10 so that the user can view the query result through the client 10 to obtain the required medicine information.

Those skilled in the art will appreciate that the frame diagram shown in fig. 1 is merely an example in which embodiments of the present application may be implemented. The scope of applicability of the embodiments of the application is not limited in any way by the framework.

It should be noted that client 10 may be any user device, existing, developing or future developed, capable of interacting with one another over any form of wired and/or wireless connection (e.g., wi-Fi, LAN, cellular, coaxial cable, etc.), including, but not limited to, existing, developing or future developed smart wearable devices, smartphones, non-smartphones, tablets, laptops, desktops, minicomputers, midrange computers, mainframe computers, and the like. Embodiments of the application are not limited in this respect. It should also be noted that server 20 in embodiments of the present application may be one example of an existing, developing or future developed device capable of performing the above-described operations. Embodiments of the application are not limited in this respect.

In order to facilitate understanding of the technical solution provided by the embodiments of the present application, a method for constructing a knowledge base provided by the embodiments of the present application will be described below with reference to the accompanying drawings.

Referring to fig. 2, which is a flowchart of a method for constructing a knowledge base according to an embodiment of the present application, as shown in fig. 2, the method may include S201-S204:

s201, acquiring a medicine entity record, wherein the medicine entity record comprises a medicine entity and medicine entity information of the medicine entity, and the medicine entity information comprises at least one medicine information field and medicine information corresponding to the medicine information field.

The drug entity record includes drug entity information corresponding to the drug entity. The drug entity may specifically be a name of a drug, and the drug entity information may be drug information related to the drug, such as information of price, component, property, indication, specification, usage, adverse reaction, contraindication, notice, and the like of the drug.

The medicine entity information at least comprises a medicine information field and medicine information corresponding to the medicine information field. The medicine information field may be used to represent a type corresponding to the medicine information, for example, may be a name of an information type corresponding to the medicine information, and the medicine information is specific content corresponding to the medicine information field. For example, the medicine information field is "indication", and the corresponding medicine information is "for alleviating symptoms such as fever, headache, sore throat, nasal obstruction, sneeze, etc. caused by the common cold or influenza".

The embodiment of the application is not limited to a specific implementation mode for acquiring the record of the medicine entity. The information can be obtained through the instruction book of each medicine, books, articles, network query results and the like related to the medicine. The structured fields in the medicine instruction book can be extracted, and the corresponding general fields are determined to be used as medicine information fields in the medicine entity records.

As an example, the medicine information field and the medicine information corresponding to the medicine information field may be expressed as [ medicine information field: medicine information ]. For example, it may be [ indication: otitis media, sinusitis, pharyngitis, and flat choulitis ], [ pharmaceutical ingredient: beta-lactam antibiotics, penicillins ].

S202, establishing a medicine knowledge base based on the medicine entity, the medicine entity record corresponding to the medicine entity and the association relation between the medicine entity and the medicine entity record.

Based on the obtained drug entity records, drug entities and drug entity information in each drug entity record may be determined.

In addition, the medicine knowledge base may further include association relations between the medicine entities. For example, a "forbidden" association relationship that cannot be taken at the same time is indicated, and a "favorable" association relationship that can be taken together is indicated. The association between each drug entity in the drug knowledge base can be constructed, so that the drug knowledge base is built according to the drug entity records and the association relationship between each drug entity. Specifically, the drug knowledge base can be established by deep learning, knowledge graph and other technologies.

For the drug entity records corresponding to drugs having the same composition but different drug names, corresponding drug entities may be established, respectively. For example, ibuprofen sustained release capsules, ibuprofen sustained release tablets and fenbixin are all medicines with ibuprofen as components. Wherein ibuprofen is the name of chemical drugs, belonging to the name of drug raw materials. Ibuprofen sustained release capsules and ibuprofen sustained release tablets are the common names of medicines. Fenbidi is the trade name of the drug. In order to facilitate the user to acquire more accurate medicine information, four medicine entities of ibuprofen, an ibuprofen sustained-release capsule, an ibuprofen sustained-release tablet and fenmust can be respectively established, and the four medicine entities respectively have corresponding medicine entity information.

In a possible implementation manner, the embodiment of the present application provides a specific implementation manner of establishing a drug knowledge base based on a drug entity, a drug entity record corresponding to the drug entity, and an association relationship between the drug entity and the drug entity record, which is described below.

And S203, determining a related knowledge base associated with the medicine knowledge base according to the medicine information history query record, wherein the related knowledge base comprises non-medicine domain entities associated with the medicine entities.

The use of drugs is also associated with other factors such as symptoms, applicable population, eating and exercise contraindications, etc. When a user inquires the medicine information, the medicine information meeting the conditions can be inquired through other related factors.

In order to determine the knowledge base associated with the medicine knowledge base from various knowledge bases, factors associated with medicines can be determined according to the medicine information history query records, so that the entity associated with the medicine entity in the non-medicine field is determined to be the related entity. And determining a relevant knowledge base corresponding to each relevant field based on the relevant entity of the relevant field. The drug information history query may specifically be a history query of a user for drug information, where the history query includes information associated with a drug entity. By analyzing the historical query records of the drug information, factors related to the drug entity can be obtained, and further, a related knowledge base related to the drug knowledge base is determined.

For example, "cold drugs that pregnant women can eat", "fever drugs specific to children? the association relationship between the specific crowd and the medicine can be determined, and the crowd knowledge base associated with the medicine knowledge base can be correspondingly determined. Similarly, the history inquiry records of medicine information can also be "what medicine can be relieved by headache, can be" can be bear inflammatory medicines after drinking "and" can be started after taking cold medicine "and the like. Correspondingly, the relevant knowledge base can be determined to further comprise a symptom knowledge base, a food material knowledge base and a movement knowledge base.

In a possible implementation manner, the embodiment of the present application further provides a specific implementation manner of determining the relevant knowledge base associated with the drug knowledge base according to the drug information history query record, which is described below.

S204, according to the medicine entity information of the medicine entity, establishing an association relation between the medicine entity and the non-medicine domain entity in the relevant knowledge base.

S205, generating a query knowledge base of medicine information based on the medicine knowledge base, the related knowledge base related to the medicine knowledge base and the association relation between the medicine entities in the medicine knowledge base and the non-medicine domain entities in the related knowledge base.

Specifically, the association relationship between the drug entity and the symptom entity in the symptom knowledge base, the crowd entity in the crowd knowledge base, the food entity in the food knowledge base and the sport entity in the sport knowledge base can be established.

After determining the relevant knowledge base, an association relationship between the entity in the relevant knowledge base and the drug entity needs to be established. The drug entity information of the drug entity has information related to the drug entity, wherein the information related to non-drug field entities such as symptom entity, crowd entity, food entity and sports entity may be included in the drug entity information. Based on the drug entity information, the association relationship between the drug entity and the non-drug domain entity in the related knowledge base can be determined and established, and the non-drug domain entity with the association relationship with the drug entity is the related entity.

Based on the drug knowledge base, the related knowledge base and the association relationship between the drug entity and the non-drug domain entity in the related knowledge base, a query knowledge base of drug information can be established. The query knowledge base comprises a medicine knowledge base, a related knowledge base related to the medicine knowledge base and an association relation between medicine entities in the medicine knowledge base and non-medicine domain entities in the related knowledge base. According to the entity and the association relation in the query knowledge base, the corresponding query can be carried out on the medicine information.

Based on the above-mentioned related contents of S201-S205, it can be known that a knowledge base integrating knowledge related to the drug can be obtained by establishing a query knowledge base including a drug knowledge base, a related knowledge base associated with the drug knowledge base, and an association relationship between drug entities in the drug knowledge base and non-drug domain entities in the related knowledge base. Therefore, the user can inquire the more accurate and comprehensive related information of the medicine based on the inquiry knowledge base of the medicine information.

It can be understood that there is an interrelation between the drugs. For example, there may be drugs that cannot be used simultaneously, or that need to be used together to be effective. When the medicine knowledge base is established, the association relation between medicine entities is also required to be established.

The embodiment of the application provides a method for establishing a specific implementation mode of a medicine knowledge base based on medicine entities, medicine entity records corresponding to the medicine entities and association relations between the medicine entities, which comprises the following two steps A1-A2:

A1, determining the association relation between the medicine entities according to medicine information corresponding to the tabu information field and/or the notice information field in the medicine entity information and medicine information corresponding to the medicine component type field.

The medicine entity information may have a tabu information field, and the medicine information corresponding to the tabu information field is the tabu information. The tabu information has a specific usage tabu associated with the drug entity. For example, the tabu information field of the drug entity information of the ibuprofen tablet is corresponding to the tabu information of the drug entity information of the aspirine or other non-steroidal anti-inflammatory drug allergic person who has cross allergic reaction to the product and asthma person allergic to aspirin, and the product can also cause bronchospasm. The product is forbidden for such patients.

The medicine entity information may have a notice field, and medicine information corresponding to the notice field is notice. Among the notes are those which require special attention for use in connection with the pharmaceutical entity. For example, the notice field in the drug entity information of "ibuprofen tablet" corresponds to a notice of "1", and for a late gestational woman, pregnancy can be prolonged, resulting in dystocia and prolonged labor. It is not suitable for pregnant women and women in lactation. 2. Has effects in inhibiting platelet aggregation, and prolonging hemorrhage time, but can disappear after stopping drug for 24 hr.

The medication information corresponding to the tabu information field or the notice information field may have information related to other medication entities associated with the medication entity, and the other medication entities having an association relationship with the medication entity may be determined by the at least one of the tabu information and the notice information. For example, the notice in the drug entity information of "gankang" is "the anticoagulation effect of the anticoagulant enhancement". Based on the notice, it may be determined that there is an association between the drug entity corresponding to "gankang" and the drug entity corresponding to the anticoagulant.

The pharmaceutical entity information may have a pharmaceutical ingredient type field therein. The medicine information corresponding to the medicine component type field is a medicine component type, and is used for determining a specific medicine component type. Based on the drug ingredient type, a drug entity belonging to the drug ingredient type may be determined.

The pharmaceutical entity having the association relationship may be determined according to at least one of the tabu information or the notice in the pharmaceutical entity information and the pharmaceutical ingredient type corresponding to the pharmaceutical ingredient type field.

The embodiment of the application provides a specific implementation manner for determining the association relationship between medicine entities according to medicine information corresponding to a tabu information field and/or a notice information field in medicine entity information and medicine information corresponding to a medicine component type field, which is described below.

A2, adding the medicine entity records into a medicine knowledge base, and associating the medicine entities with association relations aiming at the medicine entities corresponding to the medicine entity records in the medicine knowledge base.

When the medicine knowledge base is established, the medicine entity records can be added into the medicine knowledge base, and then the medicine entities with the association relationship are associated based on the medicine entities corresponding to the medicine entity records in the medicine knowledge base. And finally obtaining the medicine knowledge base comprising medicine entities, medicine entity information and association relations among the medicine entities.

Based on the above, it is known that the drug entity having the association relationship can be determined by the tabu information and/or notice in the drug entity information corresponding to the drug entity and the drug component type. Furthermore, a medicine knowledge base comprising the association relation between medicine entities can be established, so that the information in the medicine knowledge base is more perfect, and the accuracy and the comprehensiveness of the query result obtained by a user during query and the like are improved.

Further, the embodiment of the present application provides a specific implementation manner of determining an association relationship between drug entities according to drug information corresponding to a tabu information field and/or a notice field in drug entity information and drug information corresponding to a drug component type field in step A1, which specifically includes the following four steps B1-B4:

b1, reading a tabu information field and/or a notice field in medicine entity information of a first medicine entity to obtain the tabu information and/or the notice of the first medicine entity, wherein the first medicine entity is any one of the medicine entities.

And taking any one of the medicine entities in the medicine knowledge base as a first medicine entity, and reading at least one of a tabu information field or a notice field in medicine entity information of the first medicine entity. And obtaining the tabu information of the first medicine entity according to the tabu information field. The notice information of the first pharmaceutical entity may be derived from the notice field. The tabu information and the notice information have information related to the first drug entity that needs to be noted at the time of use.

B2, identifying information related to the medicine components and the association relation from the tabu information and/or the notice information of the first medicine entity, determining the identified information related to the medicine components as a target medicine component type, and determining the identified information related to the association relation as a target association relation type.

Identifying the contraindication information and/or notice information of the first medicine entity can obtain information related to medicine components and association relations.

The information related to the pharmaceutical composition is a pharmaceutical composition type referred to in the tabu information and/or the notice information. And determining the information related to the medicine components obtained by identification as a target medicine component type. For example, if the tabu information of the first drug entity "amoxicillin capsule" is "the tetracycline drug and the chloramphenicol drug cannot be taken simultaneously", the corresponding information related to the drug components obtained by recognition is "the tetracycline drug" and "the chloramphenicol drug", and the "the tetracycline drug" and "the chloramphenicol drug" are taken as the target drug component types.

The information related to the association relationship refers to a type to which the association relationship between the drug component type and the first drug entity referred to in the tabu information and/or the notice information belongs. And determining the identified information related to the association relationship as a target association relationship type.

The association relationship type may be "forbidden" or "good". "contraindicated" means that the first pharmaceutical entity and the pharmaceutical entity corresponding to the type of the target pharmaceutical ingredient cannot be taken together. "beneficial" means that simultaneous administration is required between the first drug entity and the drug entity corresponding to the type of target drug ingredient. Taking the tabu information as an example, the association relation type of the first medicine entity and the medicine entity corresponding to the tetracycline medicine and the chloramphenicol medicine is "tabu", and the "tabu" is taken as the target association component type.

And B3, acquiring a medicine entity of which the medicine component type belongs to the target medicine component type from a medicine knowledge base, constructing an association relationship between the medicine entity and the first medicine entity, and setting the association relationship type as the target association relationship type.

And reading the medicine entity information of the medicine entities except the first medicine entity in the medicine knowledge base, acquiring the medicine component type from the medicine entity information, if the medicine component type of a certain medicine entity belongs to the target medicine component type, constructing the association relationship between the medicine entity of which the medicine component type belongs to the target medicine component type and the first medicine entity, and setting the association relationship type as the target association relationship type.

For example, the first medicine entity is an amoxicillin capsule, the corresponding target medicine component types are a tetracycline medicine and a chloramphenicol medicine, and the target association relationship type is a tabu. The drug component type corresponding to the thiamphenicol is chloramphenicol, the thiamphenicol and the amoxicillin capsule can be established in association, and the association is set to be forbidden.

In one possible implementation, the drug entity information of other drug entities in the drug knowledge base may be identified by an identification model of the drug component type field to obtain the drug component type. The medicine component type can also be obtained by searching keywords or keywords corresponding to the preset medicine component type field.

In the embodiment of the application, the drug entity belonging to the target drug component type and the first drug entity can be established with an association relationship by determining the target drug component type and the target association relationship type corresponding to the first drug entity, wherein the association relationship belongs to the target association relationship type. Therefore, a relatively complete association relation between medicine entities can be established, and the comprehensiveness and accuracy of medicine information inquiry based on the inquiry knowledge base are improved.

In one possible implementation, the drug information history query record has an entity therein, and the related knowledge base to be established can be determined by performing entity identification on the drug information history query record. The embodiment of the application provides a method for determining a relevant knowledge base associated with a medicine knowledge base according to a medicine information history query record in S203, which comprises the following steps:

Entity identification is carried out on the medicine information history inquiry records, and included non-medicine field entities and types of the entities are obtained;

The drug information history query may have entities in the record that represent a particular meaning. By performing entity identification on the drug information history query record, the entity and entity type included in the drug information history query record can be obtained. The identified entity type is used to represent the type to which the entity belongs. Specifically, entity recognition can be performed on the drug information history query record through a pre-trained entity recognition model, and the entity type can be a predefined entity type which possibly appears in the drug information history query record.

The entity type obtained by recognition is the entity type related to the medicine entity, and the related knowledge base needing to be related to the medicine knowledge base can be determined from various constructed knowledge bases according to the obtained entity type.

Based on the above, the relevant knowledge base related to the medicine knowledge base is determined through the medicine information history query record, the relevant knowledge base can be determined through the query requirement of the user, the completeness of the query knowledge base of the medicine information is ensured, and the user can conveniently query the required medicine information based on the query knowledge base.

In a possible implementation manner, the related knowledge base may include a symptom knowledge base, a crowd knowledge base, a food material knowledge base and a sports knowledge base, and the embodiment of the present application further provides a specific implementation manner of establishing, according to drug entity information of a drug entity, an association relationship between the drug entity and a non-drug domain entity in the related knowledge base, including:

And establishing association relations between the medicine entity and the symptom entity in the symptom knowledge base, the crowd entity in the crowd knowledge base, the food entity in the food knowledge base and the sport entity in the sport knowledge base according to the medicine entity information of the medicine entity.

Specifically, the above-described process can be realized by:

In one possible implementation manner, in order to establish an association between a drug entity and a symptom entity in the symptom knowledge base, information corresponding to an indication field in drug entity information of a second drug entity may be read to obtain an indication of the second drug entity, a symptom entity corresponding to the indication of the second drug entity in the symptom knowledge base is obtained, and an association between the symptom entity and the second drug entity is established, where the second drug entity is any one of the drug entities.

It will be appreciated that a drug has symptoms corresponding to the treatment, i.e. the indication to which the drug corresponds. The medicine entity information of the medicine entity comprises an indication field of the medicine, and the information corresponding to the indication field is specific content of the indication. And taking any one of the drug entities as a second drug entity, and reading information corresponding to an indication field in the drug entity information of the second drug entity to obtain the indication of the second drug entity.

Taking "Gankang" as the second medicine entity as an example, the content of the indication corresponding to the indication field in the medicine entity information of "Gankang" is "suitable for relieving symptoms such as fever, headache, limb ache, sneeze, nasal discharge, nasal obstruction, pharyngalgia and the like caused by common cold and influenza". According to the information of the indication corresponding to the indication field, the indication of the second medicine entity 'Gankang' can be determined to be symptoms such as fever, headache, limb ache, sneeze, nasal discharge, nasal obstruction, pharyngalgia and the like caused by common cold and influenza.

Referring to fig. 3, the structure of a query knowledge base according to an embodiment of the present application is shown. The query knowledge base comprises a medicine knowledge base and a related knowledge base, wherein the related knowledge base is a symptom knowledge base.

The symptom knowledge base has symptom entities therein, which may correspond to individual symptoms. And determining a symptom entity corresponding to the indication of the second medicine entity from the symptom knowledge base, and establishing an association relationship between the determined symptom entity and the second medicine entity, so as to establish the association relationship between the symptom entity in the symptom knowledge base and the medicine entity in the medicine knowledge base.

Taking the second medicine entity 'Gankang' as an example, the indication of the second medicine entity 'Gankang' is symptoms such as fever, headache, limb ache, sneeze, nasal discharge, nasal obstruction, pharyngalgia and the like caused by common cold and influenza. The symptom entity 'fever', 'headache', 'limb soreness', 'sneeze', 'nasal discharge', 'nasal obstruction' and 'pharyngalgia' in the symptom knowledge base can be respectively associated with the second medicine entity 'Gankang'.

In one possible implementation manner, in order to establish an association between a drug entity and a crowd entity in a crowd knowledge base, information corresponding to a tabu information field and/or a notice field in drug entity information of a second drug entity can be read to obtain the tabu information and/or the notice of the second drug entity, information related to an applicable crowd is identified from the tabu information and/or the notice information of the second drug entity, the crowd entity corresponding to the information related to the applicable crowd in the crowd knowledge base is acquired, and the association between the crowd entity and the second drug entity is established, wherein the second drug entity is any one of the drug entities.

At least one of a tabu information field or a notice field in drug entity information of the second drug entity is read. And obtaining the tabu information of the second medicine entity according to the information corresponding to the tabu information field. And obtaining the notice information of the second medicine entity according to the information corresponding to the notice field. The contraindication information and the notice information have information related to the second drug entity that needs to be noted.

The contraindication information and/or notice information of the second medicine entity has information related to the applicable crowd related to the second medicine entity. And carrying out entity identification on the tabu information and/or the notice information of the second medicine entity to obtain related entities included in the tabu information and/or the notice information. The related entity may be a crowd entity.

For example, regarding "ibuprofen tablet" as the second pharmaceutical entity, the "pregnancy for late gestation women may be prolonged, resulting in dystocia and prolonged labor" in the notice information corresponding to the notice field in the pharmaceutical entity information of "ibuprofen tablet". It is not suitable for pregnant women and women in lactation. By carrying out entity identification on the notice information, crowd entities of pregnant women and lactating women corresponding to the second medicine entity ibuprofen tablet can be obtained.

Referring to FIG. 3, the relevant knowledge base may also include crowd knowledge bases. The crowd knowledge base has crowd entities, and the crowd entities can correspond to various crowds, such as pregnant women, children, crowds suffering from hypertension, and the like. The crowd entity may have corresponding crowd entity information, which may be information for interpreting the crowd. For example, the crowd entity information corresponding to "child" may be anyone under 18 years old.

And determining crowd entities corresponding to the second medicine entities from the crowd knowledge base, and establishing association relations between the determined crowd entities and the second medicine entities. The establishment of the association relation between the crowd knowledge base and the medicine knowledge base is realized.

Taking the second drug entity "ibuprofen tablet" as an example, the second drug entity "ibuprofen tablet" includes crowd entities of "pregnant women" and "lactating women". And respectively establishing association relations between crowd entities 'pregnant women' and 'lactating women' in the crowd knowledge base and a second medicine entity 'ibuprofen tablets'.

In one possible implementation manner, in order to establish an association relationship between a drug entity and a food material entity in a food material knowledge base, information corresponding to a tabu information field and/or a notice field in drug entity information of a second drug entity may be read to obtain tabu information and/or notice of the second drug entity, information related to the food material is identified from the tabu information and/or the notice information of the second drug entity, the food material entity corresponding to the information related to the food material in the food material knowledge base is acquired to establish the association relationship between the food material entity and the second drug entity, and the second drug entity is any one of the drug entities.

The tabu information and/or the notice information of the second medicine entity has information related to food materials related to the second medicine entity. And carrying out entity identification on the tabu information and/or the notice information of the second medicine entity to obtain related entities included in the tabu information and/or the notice information. The relevant entity may be a food entity.

For example, with "999 Ganmaoling particles" as the second pharmaceutical entity, the contraindicated information of "999 Ganmaoling particles" includes "smoke, alcohol, spicy, raw, cold, greasy food". By carrying out entity identification on the tabu information, the food material entity of 'smoke', 'wine', 'spicy', 'uncooked' and 'greasy' corresponding to the second medicine entity '999 Ganmaoling granule' can be obtained.

Referring to fig. 3, the relevant knowledge base may further include a food material knowledge base. The food material knowledge base is provided with food material entities, and the food material entities correspond to various foods. And determining a food material entity corresponding to the second medicine entity from a food material knowledge base, and establishing an association relation between the determined food material entity and the second medicine entity.

Taking the second drug entity "999 Ganmaoling granule" as an example, the food material entities included in the second drug entity "999 Ganmaoling granule" are "smoke" and "wine". Correspondingly, the '999 Ganmaoling granule' can be respectively associated with food material entities 'smoke' and 'wine' in a food material knowledge base.

It should be noted that the food material entity may also include a generic entity of a type of food. For example, seafood, greasiness, pungency, etc. The food material entity may have corresponding food material entity information including the kind of things specifically included in such food material. For example, the food entity information corresponding to "spicy" includes foods such as capsicum, shallot, ginger, leek, garlic, caraway, pepper, onion, and the like. Taking the second drug entity "999 Ganmaoling granule" as an example, the food material entities included in the second drug entity "999 Ganmaoling granule" are "spicy", "uncooked" and "greasy". Correspondingly, the ' 999 Ganmaoling granule ' and ' spicy ', ' cold and ' greasy ' in the food material knowledge base can be respectively established with association relation.

In one possible implementation manner, in order to establish an association relationship between a drug entity and a motion entity in a motion knowledge base, information corresponding to a tabu information field and/or a notice field in drug entity information of a second drug entity can be read to obtain the tabu information and/or the notice of the second drug entity, information related to motion is identified from the tabu information and/or the notice information of the second drug entity, the motion entity corresponding to the information related to motion in the motion knowledge base is acquired, and the association relationship between the motion entity and the second drug entity is established, wherein the second drug entity is any one of the drug entities.

The contraindication information and/or the notice information of the second medicine entity has information related to the second medicine entity and related to movement. And carrying out entity identification on the tabu information and/or the notice information of the second medicine entity to obtain related entities included in the tabu information and/or the notice information. The relevant entity may be a sports entity.

For example, taking "Gankang" as the second pharmaceutical entity, having "this product may cause symptoms such as sleepiness, drowsiness, etc. in the notice information in the pharmaceutical entity information of" Gankang ", drivers, vehicles, boats, and working aloft, mechanical work, and operating precision instruments are not necessary during the administration. The notice information of "feel well" is subjected to entity identification, so that the sports entity of "driving", "aloft work", "mechanical work" and "operating precise instrument" corresponding to the second medicine entity "feel well" can be obtained.

Referring to fig. 3, the relevant knowledge base may also include a motion knowledge base. The sports knowledge base is provided with sports entities, and the sports entities correspond to various sports. And determining a moving entity corresponding to the second medicine entity from the moving knowledge base, and establishing an association relation between the determined moving entity and the second medicine entity.

Taking the second drug entity "Gankang" as an example, the "Gankang" includes "driving", "aloft work", "mechanical work" and "operating a precision instrument" sports entities. And respectively establishing association relations between a moving entity 'driving', 'high-altitude operation', 'mechanical operation' and 'operation precision instrument' in the moving knowledge base and 'feel well'.

Also, it should be noted that a sporting entity may correspond to a generic term for a type of sport. The sports entity may have corresponding sports entity information, and the sports entity information may include a sports category specifically included in the sports entity. For example, the sport entity information corresponding to the "high-altitude operation" includes specific sport types such as edge, tunnel portal, climbing, hanging, crossing, etc.

In the embodiment of the application, the association relationship between the drug entity in the drug knowledge base and the entities of other related knowledge bases can be established according to the indication corresponding to the second drug entity and various entities. Based on the established association relation, the generated query knowledge base is more complete, so that a user can conveniently query medicine information through other information related to medicines, and accuracy of the queried medicine information is improved.

Based on the method for constructing the knowledge base provided by the embodiment, the embodiment of the application also provides an information query method. The information query method provided by the embodiment of the application is described below with reference to the accompanying drawings.

Referring to fig. 4, the flowchart of an information query method provided by an embodiment of the present application, as shown in fig. 4, the method may include S401 to S405:

S401, acquiring a query request of medicine information sent by a client.

When inquiring the medicine information, a user can trigger an inquiry request for generating the medicine information in the client. The client sends the query request to the corresponding server. The server obtains a query request sent by the client.

The query request includes relevant information provided by the user when the user queries for drug information. The query request may include the contents of the user's query questions. By analyzing the query request, information to be queried by the user can be determined.

And S402, identifying and obtaining at least one of a medicine entity or a non-medicine domain entity from the query request.

The drug information query request includes an entity related to drug information, and specifically may be at least one of a drug entity or a non-drug domain entity. In particular, the non-pharmaceutical field entity may comprise at least one of a symptom entity, a crowd entity, a food entity, or a sports entity.

Entity identification is carried out on the query request, so that an entity related to the medicine information can be obtained, and further the query of the medicine information is realized.

For example, if the query request is "what medicine is consumed by fever", the entity identification of the query request may result in a symptomatic entity "fever". If the query request is "what is treated with the Gankang", the medicine entity may be identified as Gankang. If the inquiry request is "the children eat the children's common cold particles and can eat the watermelons", the crowd entity "children", the medicine entity "the children's common cold particles" and the food entity "watermelons" can be obtained through identification. If the inquiry request is "drive can eat 999 Ganmaoling particles", the sportsman "drive" and the pharmaceutical entity "999 Ganmaoling particles" can be obtained by identification.

S403, determining the query intention according to the query request.

When a user inquires about medicine information, the user has an intention to inquire about medicine information. The query intention is used for reflecting the target of the drug information to be queried by the user, and the specific drug information to be acquired by the user can be determined according to the query intention. For example, if the query request is "what medicine is being eaten with fever", the corresponding query intent is the medicine name. If the inquiry request is "the driving can eat 999 Ganmaoling particles", the corresponding inquiry intention is the notice of medicine use.

The embodiment of the application is not limited to the implementation manner of determining the query intention of the query request, and in one possible implementation manner, the intention recognition of the query request can be performed through the intention recognition model obtained through pre-training.

S404, inquiring an inquiry knowledge base according to the inquiry intention and at least one of the obtained medicine entity or the non-medicine domain entity to obtain an inquiry result, wherein the inquiry knowledge base is constructed according to the method for constructing the knowledge base in any embodiment.

And based on at least one of the obtained entities identified from the query request and the determined query intention, querying in the query knowledge base established in the embodiment to obtain a corresponding query result. The query result has drug information corresponding to the query request.

In particular, the identified entities may be used to determine associated entities and related information, and the determined query intent may be used to determine queried drug information.

In a specific implementation manner, the embodiment of the application provides a specific implementation manner of querying a query knowledge base according to a query intention and at least one of the obtained drug entity or the non-drug domain entity to obtain a query result, which is described below.

And S405, sending the query result to the client.

The query result has medicine information to be acquired by the user. And sending the query result to the client so that the client displays the query result.

In order to improve the user experience, in one possible implementation, the query result may be displayed to the user through a natural language interaction manner. Specifically, the query results may be converted into a form of natural language through a language model. In addition, the query result may also be converted into a form of natural language through a preset language rule or a reply template. For example, reply templates for different types of query requests may be preset, and the determined query results are utilized to perfect the corresponding reply templates, so as to form the query results in the natural language form. In practical application, an interface with a character image of a pharmacist can be displayed on the client, and the query result is displayed to the user in the interface, so that the query process is closer to the natural language communication process.

Based on the above-described content related to S401 to S405, by identifying and analyzing the query request of the drug information, the entity included in the query request and the query intention can be determined. Based on the determined entity and the query intention, the query result of the medicine information which better meets the needs of the user can be queried, so that the obtained query result is more accurate. By utilizing the query knowledge base constructed by the method of any embodiment, the completeness of the queried knowledge base can be ensured, so that a user can query and obtain required medicine information, and the obtained medicine information is accurate.

Further, when the user performs the query, the user may perform the query of the corresponding drug information based on the self-situation. In order to make the query result more accurate, information related to the user may also be acquired, and the query result may be determined based on the information related to the user.

In one possible implementation, before querying the query knowledge base according to the query intention and at least one of the obtained pharmaceutical entity or the non-pharmaceutical domain entity, the method further includes:

Acquiring user figure information;

and obtaining the corresponding non-medicine field entity according to the figure image information of the user.

In this case, the non-pharmaceutical domain entity may be a crowd entity and/or a symptom entity.

User persona information is information related to a user that is used to more accurately determine the needs of the user. The user persona information may include information related to the gender, age, underlying medical history, etc. of the user.

The user portrait information may be personal information that the user has previously registered prior to querying using the client. Such as gender, age, underlying medical history, etc., provided by the user at registration. Or personal information of the user acquired by interacting with the user.

The user persona information may be acquired based on a query request trigger. Specifically, for example, when the user portrait information is required when the user is queried according to a query request, the user portrait information is triggered to be acquired. For example, the inquiry request of the user is '999 Ganmaoling granule how to take', and because of different taking rules of people of different age groups, in order to provide medicine information for the user more accurately, the user personage information can be obtained, and the accurate taking rule can be determined according to the user personage information.

And carrying out entity identification on the acquired user personage information to obtain crowd entities and/or symptom entities included in the user personage information. For example, the user personage information includes a disease history of the user aged 65 years with hypertension. Correspondingly, the crowd entity obtained by recognition is the old, and the symptom entity is the hypertension.

In the embodiment of the application, the crowd entity and/or symptom entity related to the user can be determined through the user personage information, so that the related information of the user can be further determined, and a more accurate query result can be determined.

Because the user queries the medicine information, the obtained query result comprises information or entities related to the medicine entity. If the medicine entity is identified in the query request, the query result can be obtained according to the medicine entity information of the medicine entity or the related entity related to the medicine entity, and if the related entity is identified in the query request, the medicine entity can be determined according to the related entity, so that the query result can be obtained.

In a possible implementation manner, the embodiment of the present application provides a method for querying a query knowledge base according to a query intention and at least one of an obtained pharmaceutical entity or a non-pharmaceutical domain entity at S404 to obtain a query result, including the following two steps C1-C2:

And C1, determining a medicine information field to be queried corresponding to the medicine entity according to the query intention when the query knowledge base is queried according to the medicine entity.

And C2, acquiring medicine information corresponding to the medicine information field to be queried based on a medicine knowledge base included in the query knowledge base, and obtaining a query result.

For the query of the information related to the medicine entity, the query knowledge base is queried, and the medicine information field to be queried corresponding to the medicine entity can be determined based on the determined query intention. The medicine information field corresponds to medicine information related to the medicine entity, and the query result corresponding to the query request can be obtained by reading the medicine information corresponding to the medicine information field to be queried.

For example, the query request is "what is being treated as" feel well ", the identified drug entity is" feel well ", and the determined query intent is an indication of the drug. The medicine information field to be queried corresponding to the "Gankang" determined based on the query intention is "indication". The medicine information corresponding to the indication of the "Gankang" is read from the query knowledge base, and the query result is "the medicine information is suitable for relieving symptoms such as fever, headache, limb ache, sneeze, nasal discharge, nasal obstruction, pharyngalgia and the like caused by common cold and influenza". For another example, the query request is "amoxicillin capsule can be eaten together with thiamphenicol", the drug entities identified are "amoxicillin capsule" and "thiamphenicol", the determined query intention is a relationship between "amoxicillin capsule" and "thiamphenicol", and the associated entity "thiamphenicol" of "amoxicillin capsule" can be determined based on the determined query intention. The association relation between the amoxicillin capsule and the thiamphenicol is read from the query knowledge base as a tabu, and a corresponding query result can be obtained as a fail.

In a possible implementation manner, based on the step C1-C2, the method can further obtain the non-drug domain entity associated with the drug entity according to the query intention based on the association relationship between the drug entity in the drug knowledge base and the non-drug domain entity in the related knowledge base included in the query knowledge base, obtain the entity information corresponding to the non-drug domain entity associated with the drug entity based on the related knowledge base included in the query knowledge base, and add the entity information into the query result.

If the drug entity is identified in the drug information query request, it is also possible to determine, according to the query intention, that the user is about to query a non-drug domain entity associated with the drug entity.

For the query of the related entities of the medicine entities, the query knowledge base can be queried, and the non-medicine domain entities associated with the medicine entities can be determined according to the determined query intention based on the association relationship between the medicine entities in the medicine knowledge base and the non-medicine domain entities in the related knowledge base. The associated non-pharmaceutical field entity may be one or more of a symptom entity, a crowd entity, a food entity, and a sports entity. Entity information corresponding to non-drug domain entities associated with drug entities can be obtained from a related knowledge base included in the query knowledge base and added into the query result.

For example, the query request is "the user can drink wine after eating the cephalosporin", the identified medicine entity is "the cephalosporin", the food entity is "the wine", and the determined query intention is the association relationship type between "the cephalosporin" and "the wine". Based on the determined query intent, the associated entity "wine" of "cephalosporin" may be determined. The association relation between the cephalosporin and the wine is read from the query knowledge base as a tabu, and a corresponding query result is obtained as a fail.

In a possible implementation manner, the embodiment of the present application provides a method for querying a query knowledge base according to a query intention and at least one of an obtained pharmaceutical entity or a non-pharmaceutical domain entity at S404 to obtain a query result, including the following three steps D1-D3:

and D1, acquiring the medicine entity associated with the non-medicine domain entity based on the association relation between the medicine entity in the medicine knowledge base and the non-medicine domain entity in the related knowledge base included in the query knowledge base when the query knowledge base is queried according to the non-medicine domain entity.

And D2, determining a medicine information field to be queried corresponding to the medicine entity according to the query intention.

And D3, acquiring medicine information corresponding to the medicine information field to be queried based on a medicine knowledge base included in the query knowledge base to obtain a query result.

If one or more of the symptom entity, crowd entity, food entity, or sports entity and other non-medicine domain entities are identified in the query request, it may be determined that the user is about to query for a medicine entity associated with the entity.

And inquiring the inquiry knowledge base, and acquiring medicine entities associated with one or more of the symptom entities, crowd entities, food entities or sports entities obtained by identification according to the determined inquiry intention based on the association relation between the medicine entities in the medicine knowledge base and the non-medicine domain entities in the related knowledge base. Further, determining a medicine information field to be queried corresponding to the medicine entity according to the query intention, and acquiring medicine information corresponding to the medicine information field to be queried from a medicine knowledge base included in the query knowledge base to obtain a query result.

For example, the inquiry request is "what medicine is sneezed for cold", the symptom entity identified is "sneeze", and the inquiry is determined to be medicine. From the query knowledge base, the medicine entities 'Gankang', '999 Ganmaoling granule' and the like associated with 'sneeze' are determined according to the query intention, and finally the query result is obtained according to the determined medicine entities.

In a possible implementation manner, on the basis of the steps D1-D3, entity information corresponding to the non-pharmaceutical field entities may be obtained based on the related knowledge base included in the query knowledge base, and added into the query result.

If one or more of the non-drug field entities such as symptom entities, crowd entities, food entities or sports entities are identified in the query request, entity information corresponding to the non-drug field entities can be obtained from a related knowledge base included in the query knowledge base, and the query result can be added.

In addition, when the obtained entities have a plurality of types, part of the medicine entities can be determined according to the part of the entities and the query intention, and then the rest of the entities are utilized to determine the related medicine entities in the part of the medicine entities, so that the query result is obtained.

For example, if the query request is "what anti-inflammatory drugs can be taken by penicillin allergic human tonsillitis", the identified symptomatic entity is "tonsillitis", the crowd entity is "penicillin allergic person", and the determined query is intended as a drug. The drug entities associated with tonsillitis can be determined to be penicillin anti-inflammatory drugs, cephalosporin anti-inflammatory drugs and the like from a query knowledge base according to query intention. And removing the penicillin anti-inflammatory agent based on the fact that the crowd entity is a penicillin allergic person, and finally determining that the related medicine entity is a cephalosporin anti-inflammatory agent and the like because the association relationship between the penicillin allergic person and the penicillin anti-inflammatory agent is a tabu, so as to obtain a query result.

In the embodiment of the application, the information or the entity to be queried is determined based on the different types of entities obtained by recognition and the query intention, so as to determine the query result. By inquiring based on the inquiry intention in the inquiry knowledge base, the result required by the user to inquire can be accurately determined, and the requirement of the user on inquiring is met.

Based on the method for constructing the knowledge base provided by the embodiment of the method, the embodiment of the application also provides a device for constructing the knowledge base, and the device is explained and illustrated below with reference to the accompanying drawings.

Referring to fig. 5, the structure of an apparatus for building a knowledge base according to an embodiment of the present application is shown. The device for constructing the knowledge base provided by the embodiment of the application comprises the following components:

A first obtaining unit 501, configured to obtain a drug entity record, where the drug entity record includes a drug entity and drug entity information of the drug entity, and the drug entity information includes at least one drug information field and drug information corresponding to the drug information field;

A first establishing unit 502, configured to establish a drug knowledge base based on the drug entity, a drug entity record corresponding to the drug entity, and an association relationship between the drug entity and the drug entity record;

a first determining unit 503, configured to determine a relevant knowledge base associated with the drug knowledge base according to a drug information history query record, where the relevant knowledge base includes non-drug domain entities associated with the drug entity;

A second establishing unit 504, configured to establish an association relationship between the drug entity and a non-drug domain entity in the relevant knowledge base according to drug entity information of the drug entity;

a generating unit 505, configured to generate a query knowledge base of drug information based on the drug knowledge base, a related knowledge base associated with the drug knowledge base, and an association relationship between drug entities in the drug knowledge base and non-drug domain entities in the related knowledge base.

In one possible implementation manner, the first establishing unit 502 includes:

In one possible implementation manner, the first determining subunit includes:

In a possible implementation manner, the first determining unit 503 is specifically configured to identify an entity of the drug information history query record, so as to obtain a non-drug domain entity and a type to which the entity belongs, where the non-drug domain entity is included in the drug information history query record;

The generating unit 505 is specifically configured to establish, according to the drug entity information of the drug entity, an association relationship between the drug entity and the symptom entity in the symptom knowledge base, the crowd entity in the crowd knowledge base, the food entity in the food knowledge base, and the sport entity in the sport knowledge base.

In one possible implementation manner, the generating unit 505 includes:

Based on the information query method provided by the method embodiment, the embodiment of the application also provides an information query device, which is explained and illustrated below with reference to the accompanying drawings.

Referring to fig. 6, the structure of an information query apparatus according to an embodiment of the present application is shown. The information query device provided by the embodiment of the application comprises:

A second obtaining unit 601, configured to obtain a query request of drug information sent by a client;

An identifying unit 602, configured to identify at least one of a pharmaceutical entity or a non-pharmaceutical domain entity from the query request;

a second determining unit 603, configured to determine a query intention according to the query request;

A query unit 604, configured to query a query knowledge base according to the query intention and at least one of the obtained drug entity or the non-drug entity to obtain a query result, where the query knowledge base is constructed according to the apparatus for constructing a knowledge base according to any one of the embodiments described above;

and the sending unit 605 is configured to send the query result to the client.

In one possible implementation, the apparatus further includes:

a third acquisition unit for acquiring the portrait information of the user;

In one possible implementation, the query unit 604 includes:

In one possible implementation, the apparatus further includes:

In one possible implementation, the query unit 604 includes:

In one possible implementation, the apparatus further includes:

Fig. 7 shows a block diagram of an apparatus 1200 for building a knowledge base. For example, device 1200 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, exercise device, personal digital assistant, and the like.

Referring to FIG. 7, device 1200 may include one or more of a processing component 1202, a memory 1204, a power component 1206, a multimedia component 1208, an audio component 1210, an input/output (I/O) interface 1212, a sensor component 1214, and a communications component 1216.

The processing component 1202 generally controls overall operation of the device 1200, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing element 1202 may include one or more processors 1220 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 1202 may include one or more modules that facilitate interactions between the processing component 1202 and other components. For example, the processing component 1202 may include a multimedia module to facilitate interaction between the multimedia component 1208 and the processing component 1202.

Memory 1204 is configured to store various types of data to support operations at device 1200. Examples of such data include instructions for any application or method operating on device 1200, contact data, phonebook data, messages, pictures, videos, and the like. The memory 1204 may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.

The power supply assembly 1206 provides power to the various components of the apparatus 1200. The power supply components 1206 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 1200.

The multimedia component 1208 includes a screen between the device 1200 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 1208 includes a front camera and/or a rear camera. The front camera and/or the rear camera may receive external multimedia data when the device 1200 is in an operational mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

The audio component 1210 is configured to output and/or input audio signals. For example, the audio component 1210 includes a Microphone (MIC) configured to receive external audio signals when the device 1200 is in an operational mode, such as a call mode, a recording mode, and a speech recognition mode. The received audio signals may be further stored in the memory 1204 or transmitted via the communications component 1216. In some embodiments, audio assembly 1210 further includes a speaker for outputting audio signals.

The I/O interface provides an interface between the processing component 1202 and a peripheral interface module, which may be a keyboard, click wheel, button, etc. These buttons may include, but are not limited to, a home button, a volume button, an activate button, and a lock button.

The sensor assembly 1214 includes one or more sensors for providing status assessment of various aspects of the device 1200. For example, the sensor assembly 1214 may detect an on/off state of the device 1200, a relative positioning of the components, such as a display and keypad of the device 1200, a change in position of the device 1200 or a component of the device 1200, the presence or absence of user contact with the device 1200, an orientation or acceleration/deceleration of the device 1200, and a change in temperature of the device 1200. The sensor assembly 1214 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 1214 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 1214 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communications component 1216 is configured to facilitate communication between the device 1200 and other devices, either wired or wireless. The device 1200 may access a wireless network based on a communication standard, such as WiFi,2G, or 3G, or a combination thereof. In one exemplary embodiment, the communication part 1216 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communications component 1216 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the apparatus 1200 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for performing the following methods:

In one possible implementation, the method includes:

Fig. 8 shows a block diagram for an information query apparatus 1300. For example, device 1300 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, exercise device, personal digital assistant, or the like.

Referring to fig. 8, the device 1300 may include one or more of a processing component 1302, a memory 1304, a power component 1306, a multimedia component 1308, an audio component 1310, an input/output (I/O) interface 1313, a sensor component 1314, and a communication component 1316.

The processing component 1302 generally controls overall operation of the device 1300, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing element 1302 may include one or more processors 1320 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 1302 can include one or more modules that facilitate interactions between the processing component 1302 and other components. For example, processing component 1302 can include multimedia modules to facilitate interactions between multimedia component 1308 and processing component 1302.

The memory 1304 is configured to store various types of data to support operations at the device 1300. Examples of such data include instructions for any application or method operating on device 1300, contact data, phonebook data, messages, pictures, video, and the like. The memory 1304 may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.

The power supply assembly 1306 provides power to the various components of the device 1300. The power components 1306 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 1300.

The multimedia component 1308 includes a screen between the device 1300 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 1308 includes a front-facing camera and/or a rear-facing camera. The front camera and/or the rear camera may receive external multimedia data when the device 1300 is in an operational mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

The audio component 1310 is configured to output and/or input audio signals. For example, the audio component 1310 includes a Microphone (MIC) configured to receive external audio signals when the device 1300 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 1304 or transmitted via the communication component 1316. In some embodiments, the audio component 1310 also includes a speaker for outputting audio signals.

The I/O interface provides an interface between the processing component 1302 and peripheral interface modules, which may be a keyboard, click wheel, buttons, etc. These buttons may include, but are not limited to, a home button, a volume button, an activate button, and a lock button.

The sensor assembly 1314 includes one or more sensors for providing status assessment of various aspects of the device 1300. For example, the sensor assembly 1314 may detect the on/off state of the device 1300, the relative positioning of the components, such as the display and keypad of the device 1300, the sensor assembly 1314 may also detect a change in position of the device 1300 or a component of the device 1300, the presence or absence of user contact with the device 1300, the orientation or acceleration/deceleration of the device 1300, and a change in temperature of the device 1300. The sensor assembly 1314 may include a proximity sensor configured to detect the presence of nearby objects in the absence of any physical contact. The sensor assembly 1314 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 1314 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 1316 is configured to facilitate communication between the device 1300 and other devices, either wired or wireless. The device 1300 may access a wireless network based on a communication standard, such as WiFi,2G or 3G, or a combination thereof. In one exemplary embodiment, the communication part 1316 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 1316 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the apparatus 1300 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for performing the following methods:

Acquiring a query request of medicine information sent by a client;

Determining a query intention according to the query request;

Inquiring an inquiry knowledge base according to the inquiry intention and at least one of the obtained medicine entity or the non-medicine domain entity to obtain an inquiry result, wherein the inquiry knowledge base is constructed according to the method for constructing the knowledge base in any embodiment;

And sending the query result to the client.

Acquiring user figure information;

In one possible implementation, the method further includes:

Fig. 9 is a schematic structural diagram of a server according to an embodiment of the present invention. The server 1400 can vary widely from configuration to configuration or performance to performance, and can include one or more central processing units (central processing units, CPUs) 1422 (e.g., one or more processors) and memory 1432, one or more storage mediums 1430 (e.g., one or more mass storage devices) that store applications 1442 or data 1444. Wherein the memory 1432 and storage medium 1430 can be transitory or persistent storage. The program stored in the storage medium 1430 may include one or more modules (not shown), each of which may include a series of instruction operations on a server. Still further, the central processor 1422 may be configured to communicate with a storage medium 1430 to execute a series of instruction operations in the storage medium 1430 on the server 1400 for performing the method of constructing a knowledge base or the information query method described above.

The server 1400 may also include one or more power supplies 1426, one or more wired or wireless network interfaces 1450, one or more input/output interfaces 1456, one or more keyboards 1456, and/or one or more operating systems 1441, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, and the like.

It should be noted that, in the present description, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system or device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant points refer to the description of the method section.

It should be understood that in the present application, "at least one (item)" means one or more, and "a plurality" means two or more. "and/or" is used to describe an association relationship of an associated object, and indicates that three relationships may exist, for example, "a and/or B" may indicate that only a exists, only B exists, and three cases of a and B exist simultaneously, where a and B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one of a, b or c may represent a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

It is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of constructing a knowledge base, the method comprising:

acquiring a medicine entity record, wherein the medicine entity record comprises a medicine entity and medicine entity information of the medicine entity, the medicine entity information comprises at least one medicine information field and medicine information corresponding to the medicine information field, the medicine information field is used for representing the type corresponding to the medicine information, and the medicine information is specific content corresponding to the medicine information field corresponding to the medicine information;

Based on the medicine entities, the medicine entity records corresponding to the medicine entities and the association relation between the medicine entities, establishing a medicine knowledge base, wherein the medicine knowledge base comprises the steps of determining the association relation between the medicine entities according to medicine information corresponding to tabu information fields and/or notice fields in the medicine entity information and medicine information corresponding to medicine component type fields;

determining a related knowledge base associated with the medicine knowledge base according to the type of the entity, wherein the related knowledge base comprises a non-medicine domain entity which is associated with the medicine entity, and the related knowledge base comprises a symptom knowledge base, a crowd knowledge base, a food material knowledge base and a movement knowledge base;

Establishing association relations between the drug entity and the symptom entity in the symptom knowledge base, the crowd entity in the crowd knowledge base, the food entity in the food knowledge base and the sport entity in the sport knowledge base according to the drug entity information of the drug entity;

Generating a query knowledge base of medicine information based on the association relationship between the medicine entity and the symptom entity in the symptom knowledge base, the crowd entity in the crowd knowledge base, the food entity in the food knowledge base and the movement entity in the movement knowledge base;

wherein the second drug entity is any one of the drug entities, and the method for constructing the association relationship between the symptom entity and the second drug entity comprises the following steps:

Acquiring a symptom entity corresponding to the indication of the second medicine entity in the symptom knowledge base, and constructing an association relationship between the symptom entity and the second medicine entity;

the method for constructing the association relationship between the crowd entity and the second medicine entity comprises the following steps:

acquiring crowd entities corresponding to the information related to the applicable crowd in the crowd knowledge base, and constructing an association relationship between the crowd entities and the second medicine entity;

The method for constructing the association relationship between the food material entity and the second medicine entity comprises the following steps:

Acquiring food material entities corresponding to the information related to the food materials in the food material knowledge base, and constructing association relations between the food material entities and the second medicine entities;

The method for constructing the association relationship between the sports entity and the second medicine entity comprises the following steps:

2. The method according to claim 1, wherein the determining the association relationship between the drug entities according to the drug information corresponding to the tabu information field and/or the notice field and the drug information corresponding to the drug component type field in the drug entity information includes:

3. An information query method, the method comprising:

Acquiring a query request of medicine information sent by a client;

Determining a query intention according to the query request;

Inquiring an inquiry knowledge base according to the inquiry intention and at least one of the obtained medicine entity or the non-medicine domain entity to obtain an inquiry result, wherein the inquiry knowledge base is constructed according to the method for constructing the knowledge base in claim 1 or 2;

And sending the query result to the client.

4. A method according to claim 3, wherein prior to querying a query knowledge base for query results based on the query intent and the resulting at least one of a pharmaceutical entity or a non-pharmaceutical domain entity, the method further comprises:

Acquiring user figure information;

5. The method according to claim 3 or 4, wherein the querying the query knowledge base according to the query intention and at least one of the obtained pharmaceutical entity or the non-pharmaceutical domain entity to obtain a query result comprises:

6. The method of claim 5, wherein the method further comprises:

7. The method according to claim 3 or 4, wherein the querying the query knowledge base according to the query intention and at least one of the obtained pharmaceutical entity or the non-pharmaceutical domain entity to obtain a query result comprises:

8. The method of claim 7, wherein the method further comprises:

9. An apparatus for building a knowledge base, the apparatus comprising:

The first acquisition unit is used for acquiring a medicine entity record, wherein the medicine entity record comprises a medicine entity and medicine entity information of the medicine entity, the medicine entity information comprises at least one medicine information field and medicine information corresponding to the medicine information field, the medicine information field is used for representing the type corresponding to the medicine information, and the medicine information is specific content corresponding to the medicine information field;

the device comprises a first determining unit, a second determining unit, a third determining unit and a fourth determining unit, wherein the first determining unit is used for performing entity identification on a medicine information history inquiry record to obtain a non-medicine domain entity and a type of the entity, which are included in the medicine information history inquiry record, and determining a related knowledge base related to the medicine knowledge base according to the type of the entity, the related knowledge base comprises a non-medicine domain entity related to the medicine entity, and the related knowledge base comprises a symptom knowledge base, a crowd knowledge base, a food knowledge base and a movement knowledge base;

The second establishing unit is used for establishing association relations among the medicine entity, the symptom entity in the symptom knowledge base, the crowd entity in the crowd knowledge base, the food entity in the food knowledge base and the sports entity in the sports knowledge base according to the medicine entity information of the medicine entity;

The generation unit is used for generating a query knowledge base of medicine information based on the association relationship between the medicine entity and the symptom entity in the symptom knowledge base, the crowd entity in the crowd knowledge base, the food entity in the food knowledge base and the movement entity in the movement knowledge base;

Acquiring a moving entity corresponding to the information related to the movement in the movement knowledge base, and constructing an association relationship between the moving entity and the second medicine entity;

Wherein the first establishing unit includes:

10. The apparatus of claim 9, wherein the first determination subunit comprises:

11. An information query apparatus, the apparatus comprising:

the query unit is used for querying a query knowledge base according to the query intention and at least one of the obtained medicine entity or the non-medicine domain entity to obtain a query result, wherein the query knowledge base is constructed according to the device for constructing the knowledge base of claim 1 or 2;

and the sending unit is used for sending the query result to the client.

12. The apparatus of claim 11, wherein the apparatus further comprises:

a third acquisition unit for acquiring the portrait information of the user;

13. The apparatus according to claim 11 or 12, wherein the querying element comprises:

14. The apparatus of claim 13, wherein the apparatus further comprises:

15. The apparatus according to claim 11 or 12, wherein the querying element comprises:

16. The apparatus of claim 15, wherein the apparatus further comprises:

17. An apparatus for building a knowledge base, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs comprising a method for performing the building of a knowledge base as claimed in claim 1 or 2.

18. An apparatus for information querying, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising means for performing the information querying method as claimed in any of claims 3-8.

19. A computer readable medium having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform the method of building a knowledge base of claim 1 or 2, or to perform the information query method of any of claims 3-8.