CN110737430A - Decision-making method and device - Google Patents
Decision-making method and deviceDownload PDFInfo
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- CN110737430A CN110737430ACN201910865998.4ACN201910865998ACN110737430ACN 110737430 ACN110737430 ACN 110737430ACN 201910865998 ACN201910865998 ACN 201910865998ACN 110737430 ACN110737430 ACN 110737430A
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Abstract
Description
Technical Field
The application relates to the technical field of decision engine platforms, in particular to decision methods and devices.
Background
With the development of banking business, the system gradually develops towards platformization, productization and servitization.
At present, a decision system commonly used by banks is a three-party commercial product, the requirement on the skills of policy development is high, business personnel cannot finish configuration, test and deployment of policies independently, professional technical post personnel are required to assist in completing development and deployment, the communication, research and development and test periods are long, and the updating iteration efficiency of the policies is seriously influenced.
Disclosure of Invention
The present application aims to provide decision-making methods and devices to solve the problem in the prior art that the update iteration efficiency of a policy is seriously affected due to long communication, research, development and test periods.
In order to achieve the above purpose, the technical solutions adopted in the embodiments of the present application are as follows:
, the embodiment of the present application provides decision method applied to a decision engine platform, the method includes:
the server receives at least parameters sent by the client device;
the server generates a decision tree, rules and a model according to at least parameters and generates a rule set according to the rules;
the server creates a flow according to the rule set, the decision tree and the model, and obtains a decision result according to the flow calculation;
and the server sends the decision result to the client equipment, and the client equipment is used for receiving and displaying the decision result.
Optionally, the rules include at least rules including general type rules, tree rules, and model rules.
Optionally, the at least parameters include a base parameter and/or a derivative parameter.
Optionally, the sending, by the server, the decision result to the client device further includes:
and if the decision result is abnormal, the server returns an early warning instruction to the client equipment, wherein the early warning instruction is the decision result.
In a second aspect, another embodiment of the present application further provides decision-making methods applied to a decision-making engine platform, the method including:
the client device receives target data, wherein the target data comprises at least parameters;
the client device sends the target data to a server; the server is used for generating a rule set, a decision tree and a model according to the target equipment, creating a flow according to the generated rule set, the decision tree and the model, calculating according to the flow to obtain a decision result and sending the decision result to the client equipment;
and the client equipment receives and displays the decision result sent by the server.
Optionally, before the client device receives the target data, the method further includes:
the client equipment sends the user identity to the server, and the server is used for verifying the user identity and sending a verification result to the client equipment;
the client device receives the verification result sent by the server;
and if the verification result passes, the client device receives target data input by the verified user, wherein the target data is data in the authority range input by the verified user.
Optionally, after the client terminal receives the verification result sent by the server, the method further includes:
if the verification result is not passed, the client equipment sends out an early warning signal; and the early warning signal is an early warning instruction sent by the server and received by the client equipment after the verification result fails.
In a third aspect, another embodiment of the present application provides decision making apparatuses for use in a decision engine platform, where the apparatus includes a receiving module, a generating module, a calculating module, and a sending module, where:
the receiving module is used for receiving at least parameters sent by the client device;
the generating module is used for generating a decision tree, rules and models according to at least parameters and generating a rule set according to the rules;
the calculation module is used for creating a flow according to the rule set, the decision tree and the model and calculating according to the flow to obtain a decision result;
the sending module is used for sending the decision result to the client device, and the client device is used for receiving and displaying the decision result.
In a fourth aspect, another embodiment of the present application further provides decision-making apparatuses, which are applied to a decision-making engine platform, and the apparatus includes a receiving module, a sending module, and a displaying module, wherein:
the receiving module is used for receiving target data, wherein the target data comprises at least parameters;
the sending module is used for sending the target data to a server; the server is used for generating a rule set, a decision tree and a model according to the target equipment, creating a flow according to the generated rule set, the decision tree and the model, calculating according to the flow to obtain a decision result and sending the decision result to the client equipment;
and the display module is used for receiving and displaying the decision result sent by the server.
Optionally, the apparatus further comprises: and the early warning module is used for sending an early warning signal by the client equipment if the verification result fails.
In a fifth aspect, another embodiment of the present application provides decision-making devices, including a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the decision-making device is operating, the processor executing the machine-readable instructions to perform the steps of the method as described in above.
In a sixth aspect, another embodiment of the present application provides decision-making devices, including a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the decision-making device is operated, the processor and the storage medium communicate via the bus, and the processor executes the machine-readable instructions to perform the steps of the method according to the second aspect.
In a seventh aspect, another embodiment of the present application provides storage media, where the storage media stores a computer program that, when executed by a processor, performs the steps of the method of aspect .
In an eighth aspect, another embodiment of the present application provides storage media having stored thereon a computer program that, when executed by a processor, performs the steps of the method according to the second aspect.
The method has the advantages that by the aid of the decision method, at least parameters sent by the client side equipment are received, the decision tree, the model and the rule are generated according to at least parameters, the rule set is generated according to the rule, the flow is created according to the rule set, the decision tree and the model, the decision result is obtained according to flow calculation and is sent to the client side equipment, the decision result is displayed through the client side equipment, automatic analysis of rule business logic is conducted through the server, business strategy personnel can directly complete strategy model configuration development on the client side equipment through parameter and rule input, technical personnel do not need to participate, communication cost is reduced, maintenance cost is reduced, response efficiency of model strategies is increased, risk factors in strategy model development are reduced, and labor cost is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic flow chart of a decision-making method according to an embodiment of the present application ;
FIG. 2 is a schematic flow chart diagram illustrating a decision-making method according to another embodiment of the present application;
FIG. 3 is a schematic flow chart of a decision-making method according to another embodiment of the present application;
FIG. 4 is a schematic flow chart diagram illustrating a decision-making method according to another embodiment of the present application;
fig. 5 is a schematic structural diagram of a decision device according to an embodiment of the present application ;
FIG. 6 is a schematic diagram of a decision device according to another embodiment of the present application;
FIG. 7 is a schematic diagram of a decision device according to another embodiment of the present application;
fig. 8 is a schematic structural diagram of a decision-making device according to an embodiment of the present application ;
fig. 9 is a schematic structural diagram of a decision-making device according to an embodiment of this application .
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are partial embodiments of the present application , but not all embodiments.
Fig. 1 is a flow chart illustrating a decision-making method provided by an embodiment of the present application , where the decision-making method can be executed by a server with data processing capability, such as any server with data processing capability, for example, a tablet, a laptop, a palm computer, a desktop computer, and the like, as shown in fig. 1, the method can include:
s101, the server receives at least parameters sent by the client device.
The parameters of different channels (service users) are different, for example, employees in different parts can only view and select required parameters within their own authority range, and modifications of the parameters of different channels do not affect each other, the parameters include basic parameters and derived parameters, wherein the basic parameters are data entries used for determining current decisions according to business differences of each product, and parameter names, the derived parameters are corresponding classifications made according to types and usages of data, the derived data are not commonly used in different processes (divided into data used in the processes and decision result output data), the types of the parameters received by the server and sent by the client are at least parameter types including integer (int), length (long), double (double), and string (string), can be at least parameters of types, and can also be parameters of several different types, and the specific entry types and the number of the parameters are designed according to needs of users, and the application is not limited herein.
S102, the server generates decision trees, rules and models according to at least parameters and generates rule sets according to the rules.
Each channel (service user) can be oriented to different customer groups according to own business characteristics, different business rules are formulated for qualitative analysis of customers, and online verification and historical data callback of a single rule are supported.
The rule set is a generic term of the rule set, rule sets are formed by grouping a plurality of rules, the rule responsible for managing the list is a set or a carrier of a single rule, and the rule is deployed through the rule set.
The method comprises the steps of establishing a plurality of models, establishing a plurality of channels, establishing a plurality of parameters, establishing a plurality of related models, establishing a score card, a decision tree, a crown selection and the like, wherein the score card is divided according to sections of parameters to be entered, different parameters are distributed with different score data in different sections, and a final score result is obtained through summarizing a plurality of fields and is used for quantitative analysis of clients, and establishing models, which are mainly used for solving judgment items output by a multi-parameter control result and are used for model items such as money amount, term number and the like.
S103: and the server creates a flow according to the rule set, the decision tree and the model, and obtains a decision result according to flow calculation.
The flow is a carrier of related strategies such as a rule set, a decision tree, a model and the like, is a wind control flow in a decision engine platform, the trend of the control flow is judged according to nodes, the rule set, the decision tree and the model are connected in series in a flow mode, the whole flow is communicated according to the result of each node, and the decision result is output by the system .
S104: and the server sends the decision result to the client equipment, and the client equipment is used for receiving and displaying the decision result.
By adopting the decision method provided by the application, the client equipment receives at least parameters sent by the client equipment, the decision tree, the model and the rule are generated according to at least parameters, the rule set is generated according to the rule, the flow is created according to the rule set, the decision result is obtained according to the flow calculation and is sent to the client equipment, the decision result is displayed through the client equipment, the server automatically analyzes the rule service logic, the service policy personnel can directly complete the configuration and development of the policy model on the client equipment through inputting the parameters and the rules, technical personnel do not need to participate, the communication cost is reduced, the maintenance cost is reduced, the response efficiency of the model policy is increased, the risk factors in the development of the policy prime model are reduced, and the labor cost is reduced.
Optionally, S104 further includes: and if the decision result is abnormal, the server returns an early warning instruction to the client equipment, wherein the early warning instruction is the decision result.
In addition, if an abnormality is detected in the parameter participating process, the server also returns an early warning instruction to the client device and returns the early warning instruction in time, and the early warning instruction informs relevant business personnel of problems occurring in the current flow and part where the current.
Fig. 2 is a decision method according to another embodiment of the present application, applied to a decision engine platform, as shown in fig. 2, the method including:
s201: the client device receives the target data.
Wherein the target data comprises at least parameters.
The target data can be selected from preset parameters by a user on any terminal equipment with a display function, wherein the preset parameters comprise basic parameters and derivative parameters, and the terminal equipment can be any terminal equipment with a display function, such as a tablet, a mobile phone, a notebook, a desktop and the like.
S202: the client device sends the target data to the server.
The server is used for generating a rule set, a decision tree and a model according to the target equipment, creating a flow according to the generated rule set, decision tree and model, calculating a decision result according to the flow, and sending the decision result to the client equipment.
S203: and the client equipment receives and displays the decision result sent by the server.
Fig. 3 is a schematic flow chart of a decision method according to another embodiment of the present application, and as shown in fig. 3, before step S201, the method further includes:
s204: the client device sends the user identity to the server, and the server is used for verifying the user identity and sending a verification result to the client device.
Before the user selects the parameters, the user identity needs to be verified, whether the user identity is safe or not is confirmed, and the authority of the user is confirmed, so that the safety of the system is ensured.
S205: and judging whether the verification is passed.
And the client terminal receives the verification result sent by the server.
If the verification result passes, step S101 is executed, and the client device receives the target data input by the verified user.
The target data is data in the authority range input by the verified user, the selectable parameters of different channels are different, the employees in different departments can only check and select the required parameters in the authority range, and the modification of the parameters of different channels cannot affect each other.
Fig. 4 is a flowchart illustrating a decision method according to another embodiment of the present application, as shown in fig. 4, after S205, the method further includes, if the verification result fails, the client device executing S206 to issue an early warning signal.
The verification fails, namely that the current user does not have the authority to use the decision method, and the early warning signal is an early warning instruction which is received by the client device and sent by the server after the verification result fails.
Alternatively, the alert signal may be a text reminder, for example, returning a "current user identity not verified! Authentication failure! "; or return a voice prompt, such as a beep to remind the current user that the identity is not verified; text reminding and voice reminding can also be returned; the specific form of the warning signal is set according to the user requirement, and is not limited to the above modes, and the application is not limited thereto.
The decision method provided by the application can be directly operated by service personnel, professional tools do not need to be caught, strategy technical support post personnel are completely released, efficient early warning can be implemented to monitor the entering-parameter safety and decision results, and the safe operation of the process is ensured.
Fig. 5 is a schematic structural diagram of a decision apparatus according to an embodiment of this application , as shown in fig. 5, the apparatus includes a receivingmodule 301, agenerating module 302, a calculatingmodule 303, and a sendingmodule 304, where:
areceiving module 301, configured to receive at least parameters sent by a client device.
Thegenerating module 302 is configured to generate a decision tree, a rule and a model according to at least parameters, and generate a rule set according to the rule.
The calculatingmodule 303 is configured to create a flow according to the rule set, the decision tree and the model, and calculate a decision result according to the flow.
The sendingmodule 304 is configured to send the decision result to the client device, and the client device is configured to receive and display the decision result.
The above-mentioned apparatus is used for executing the method provided by the foregoing embodiment, and the implementation principle and technical effect are similar, which are not described herein again.
Fig. 6 is a schematic structural diagram of a decision device according to another embodiment of the present application, applied to a decision engine platform, as shown in fig. 6, the decision device includes a receivingmodule 401, a sendingmodule 402, and adisplay module 403, where:
the receivingmodule 401 is configured to receive target data, where the target data includes at least parameters.
A sendingmodule 402, configured to send target data to a server; the server is used for generating a rule set, a decision tree and a model according to the target equipment, creating a flow according to the generated rule set, decision tree and model, calculating a decision result according to the flow, and sending the decision result to the client equipment.
And adisplay module 403, configured to receive and display a decision result sent by the server.
Fig. 7 is a schematic structural diagram of a decision-making apparatus according to another embodiment of the present application, where the apparatus shown in fig. 7 further includes an early-warning module 404, configured to send an early-warning signal if a verification result fails.
The above-mentioned apparatus is used for executing the method provided by the foregoing embodiment, and the implementation principle and technical effect are similar, which are not described herein again.
These modules may be or more Integrated circuits configured to implement the above methods, such as or more Application Specific Integrated Circuits (ASICs), or more microprocessors (DSPs), or more Field Programmable Gate Arrays (FPGAs), etc. again, for example, when a module is implemented in the form of processing element scheduler code, the processing element may be a general purpose processor, such as a Central Processing Unit (CPU) or other processor that may invoke the program code.
Fig. 8 is a schematic structural diagram of a decision device according to an embodiment of this application , where an obtaining device of the decision device may be integrated in a terminal device or a chip of the terminal device, and the terminal may be a computing device with an image processing function.
The decision device may comprise: aprocessor 501, astorage medium 502, and abus 503.
Theprocessor 501 is used for storing a program, and theprocessor 501 calls the program stored in thestorage medium 502 to execute the above method embodiment. The specific implementation and technical effects are similar, and are not described herein again.
Fig. 9 is a schematic structural diagram of a decision device according to another embodiment of the present application, where an obtaining device of the decision device may be integrated in a terminal device or a chip of the terminal device, and the terminal may be a computing device with an image processing function.
The decision device may comprise: a processor 601, a storage medium 602, and a bus 603.
The processor 601 is used for storing a program, and the processor 601 calls the program stored in the storage medium 602 to execute the above method embodiments. The specific implementation and technical effects are similar, and are not described herein again.
Optionally, the present application also provides program products, such as a storage medium, having stored thereon a computer program, including a program, which when executed by a processor, performs the method embodiment described above with reference to fig. 1.
Optionally, the present application also provides program products, such as a storage medium, having stored thereon a computer program, including a program, which when executed by a processor, performs the method embodiments described above with reference to fig. 2-3.
For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units into logical functional divisions may be realized in other ways, for example, multiple units or components may be combined or integrated into another systems, or features may be omitted or not executed, in another point, the shown or discussed coupling or direct coupling or communication connection between each other may be through interfaces, and the indirect coupling or communication connection of the apparatuses or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in places, or may also be distributed on multiple network units.
In addition, functional units in the embodiments of the present application may be integrated into processing units, or each unit may exist alone physically, or two or more units are integrated into units.
The software functional unit is stored in storage media and includes a plurality of instructions for enabling computer devices (such as personal computers, servers, or network devices) or processors (english: processors) to execute part of the steps of the methods according to the embodiments of the present application.
Claims (10)
1, decision method applied to decision engine platform, characterized in that, the method includes:
the server receives at least parameters sent by the client device;
the server generates a decision tree, rules and a model according to at least parameters and generates a rule set according to the rules;
the server creates a flow according to the rule set, the decision tree and the model, and obtains a decision result according to the flow calculation;
and the server sends the decision result to the client equipment, and the client equipment is used for receiving and displaying the decision result.
2. The method of claim 1, wherein the rules include at least of the following rules, -type rules, tree-type rules, and model-type rules.
3. The method of claim 1, wherein the at least parameters comprise basic parameters and/or derived parameters.
4. The method of claim 1, wherein the server sending the decision result to a client device further comprises:
and if the decision result is abnormal, the server returns an early warning instruction to the client equipment, wherein the early warning instruction is the decision result.
5, decision method applied to decision engine platform, characterized in that the method comprises:
the client device receives target data, wherein the target data comprises at least parameters;
the client device sends the target data to a server; the server is used for generating a rule set, a decision tree and a model according to the target equipment, creating a flow according to the generated rule set, the decision tree and the model, calculating according to the flow to obtain a decision result and sending the decision result to the client equipment;
and the client equipment receives and displays the decision result sent by the server.
6. The method of claim 5, wherein prior to the client device receiving the target data, further comprising:
the client equipment sends the user identity to the server, and the server is used for verifying the user identity and sending a verification result to the client equipment;
the client device receives the verification result sent by the server;
and if the verification result passes, the client device receives target data input by the verified user, wherein the target data is data in the authority range input by the verified user.
7. The method of claim 6, wherein after the client terminal receives the verification result sent by the server, the method further comprises:
if the verification result is not passed, the client equipment sends out an early warning signal; and the early warning signal is an early warning instruction sent by the server and received by the client equipment after the verification result fails.
8, decision-making devices applied to decision engine platform, characterized in that the device comprises a receiving module, a generating module, a calculating module and a sending module, wherein:
the receiving module is used for receiving at least parameters sent by the client device;
the generating module is used for generating a decision tree, rules and models according to at least parameters and generating a rule set according to the rules;
the calculation module is used for creating a flow according to the rule set, the decision tree and the model and calculating according to the flow to obtain a decision result;
the sending module is used for sending the decision result to the client device, and the client device is used for receiving and displaying the decision result.
The decision making device applied to a decision engine platform is characterized by comprising a receiving module, a sending module and a display module, wherein:
the receiving module is used for receiving target data, wherein the target data comprises at least parameters;
the sending module is used for sending the target data to a server; the server is used for generating a rule set, a decision tree and a model according to the target equipment, creating a flow according to the generated rule set, the decision tree and the model, calculating according to the flow to obtain a decision result and sending the decision result to the client equipment;
and the display module is used for receiving and displaying the decision result sent by the server.
10. The apparatus of claim 9, wherein the apparatus further comprises: and the early warning module is used for sending an early warning signal by the client equipment if the verification result fails.
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