Disclosure of Invention
To solve or at least partially solve the above technical problems, embodiments of the present disclosure provide a question and answer result output method, apparatus, storage medium, and program product.
A first aspect of an embodiment of the present disclosure provides a question-answer result output method, including:
Acquiring text information input by a user, and determining an initial service data packet according to the text information input by the user, wherein the initial service data packet is used for representing service data information associated with the text information input by the user;
Acquiring a preset semantic mapping dictionary and an index dictionary, and converting the initial service data packet according to the preset semantic mapping dictionary and the index dictionary to obtain a target service data packet;
Inputting the text information input by the user, the index dictionary, the target business data packet, a first knowledge base and a second knowledge base into a preset big model, and outputting a question-answer result based on the preset big model, wherein the first knowledge base is a basic knowledge base related to the text information input by the user, and the second knowledge base is a similar knowledge base related to the text information input by the user.
In one example, the converting the initial service data packet according to the preset semantic mapping dictionary and the index dictionary to obtain a target service data packet includes:
performing first conversion processing on the initial service data packet according to the preset semantic mapping dictionary to obtain an intermediate service data packet;
and performing second conversion processing on the intermediate service data packet according to the index dictionary to obtain the target service data packet.
In one example, the performing a first conversion process on the initial service data packet according to the preset semantic mapping dictionary to obtain an intermediate service data packet includes:
acquiring first semantic information and second semantic information in the preset semantic mapping dictionary, and searching the first semantic information in the initial service data packet, wherein the first semantic information and the second semantic information have a corresponding relation;
and replacing the first semantic information in the initial service data packet with the second semantic information to obtain the intermediate service data packet.
In one example, the performing, according to the index dictionary, a second conversion process on the intermediate service data packet to obtain the target service data packet includes:
Acquiring the second semantic information and the number information in the index dictionary, and searching the second semantic information in the intermediate service data packet, wherein the second semantic information and the number information have a corresponding relation;
And replacing the second semantic information in the intermediate service data packet with the number information to obtain the target service data packet.
In one example, the determining an initial service data packet according to the text information input by the user includes:
Inputting the text information input by the user into a classification model, and determining the business category to which the text information input by the user belongs based on the classification model;
and identifying keywords in the text information input by the user based on the classification model, and determining the initial service data packet in the service category according to the keywords.
In one example, the second knowledge base is a similar knowledge base associated with text information entered by the user, comprising:
Inputting the text information input by the user into an expansion knowledge base, and searching text information similar to the text information input by the user in the expansion knowledge base;
And determining the similar text information as the second knowledge base.
In one example, the determining the similar text information as the second knowledge base includes:
And combining the similar text information which is larger than a threshold value to obtain the second knowledge base.
A second aspect of the embodiments of the present disclosure provides a question-answer result output apparatus, including:
The system comprises an acquisition module, a service data processing module and a service data processing module, wherein the acquisition module is used for acquiring text information input by a user and determining an initial service data packet according to the text information input by the user, wherein the initial service data packet is used for representing service data information related to the text information input by the user;
The processing module is used for acquiring a preset semantic mapping dictionary and an index dictionary, and converting the initial service data packet according to the preset semantic mapping dictionary and the index dictionary to obtain a target service data packet;
The output module is used for inputting the text information input by the user, the index dictionary, the target business data packet, a first knowledge base and a second knowledge base into a preset big model, and outputting a question-answer result based on the preset big model, wherein the first knowledge base is a basic knowledge base associated with the text information input by the user, and the second knowledge base is a similar knowledge base associated with the text information input by the user.
A third aspect of the disclosed embodiments provides an electronic device comprising a processor and a memory, wherein the memory has stored therein a computer program which, when executed by the processor, performs the method of the first aspect described above.
A fourth aspect of the disclosed embodiments provides a computer readable storage medium having stored therein a computer program which, when executed by a processor, can implement the method of the first aspect described above.
A fifth aspect of the disclosed embodiments provides a computer program product comprising a computer program which, when executed by a processor, implements the method as described in the first aspect.
The embodiment of the disclosure provides a question and answer result output method, equipment, a storage medium and a program product, wherein the method comprises the steps of obtaining text information input by a user, determining an initial service data packet according to the text information input by the user, wherein the initial service data packet is used for representing service data information related to the text information input by the user, obtaining a preset semantic mapping dictionary and an index dictionary, converting the initial service data packet according to the preset semantic mapping dictionary and the index dictionary to obtain a target service data packet, inputting the text information input by the user, the target service data packet, a first knowledge base and a second knowledge base into a preset large model, and outputting a question and answer result based on the preset large model, wherein the first knowledge base is a basic knowledge base related to the text information input by the user, and the second knowledge base is a similar knowledge base related to the text information input by the user. By adopting the technical scheme, the service data information can be queried in real time, and the response speed of the service data information and the accuracy of response content are improved.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein, and it is apparent that the embodiments in the specification are only some, rather than all, of the embodiments of the present disclosure.
Fig. 1 is a flowchart of a question and answer result output method according to an embodiment of the disclosure, which may be performed by an electronic device. The electronic device may be understood as a device such as a mobile phone, tablet, notebook, desktop, smart television, etc., by way of example. As shown in fig. 1, the method provided in this embodiment includes the following steps:
S101, acquiring text information input by a user, and determining an initial service data packet according to the text information input by the user, wherein the initial service data packet is used for representing service data information associated with the text information input by the user.
The embodiment can be executed by an application program built in the electronic device, and specifically, can be executed by intelligent customer service in the application program. The text information input by the user is the business related questions to be consulted by the user. In this embodiment, text information input by a user is input to the intelligent customer service. The initial service data packet is used for representing service data information associated with text information input by a user, wherein the initial service data packet is a code file related to the service data.
S102, acquiring a preset semantic mapping dictionary and an index dictionary, and converting the initial service data packet according to the preset semantic mapping dictionary and the index dictionary to obtain a target service data packet.
In one example, the preset semantic mapping dictionary is a mapping relationship between different semantic information. For example, "name" corresponds to "name". The index dictionary is a mapping relation between semantic information and number information, for example, "name" corresponds to number information "1".
In one example, the data volume of the target traffic data packet is less than the data volume of the initial traffic data packet. And converting the initial service data packet through a preset semantic mapping dictionary and an index dictionary, so that the data volume of the initial service data packet is reduced, and a target service data packet is obtained.
S103, inputting text information input by a user, an index dictionary, a target business data packet, a first knowledge base and a second knowledge base into a preset large model, and outputting a question-answer result based on the preset large model, wherein the first knowledge base is a basic knowledge base associated with the text information input by the user, and the second knowledge base is a similar knowledge base associated with the text information input by the user.
In one example, the first knowledge base is a base knowledge base associated with text information entered by a user, wherein the base knowledge base is business related base data information. Such as the name of the service and basic data information of the service. The second knowledge base is a similar knowledge base associated with text information entered by the user.
In this embodiment, text information, an index dictionary, a target service data packet, a first knowledge base and a second knowledge base input by a user are input into a preset large model, so that the preset large model combines the text information, the index dictionary, the target service data packet, the first knowledge base and the second knowledge base input by the user to determine a question-answer result together.
The embodiment of the disclosure provides a question and answer result output method, which comprises the steps of obtaining text information input by a user, determining an initial service data packet according to the text information input by the user, wherein the initial service data packet is used for representing service data information related to the text information input by the user, obtaining a preset semantic mapping dictionary and an index dictionary, converting the initial service data packet according to the preset semantic mapping dictionary and the index dictionary to obtain a target service data packet, inputting the text information input by the user, the index dictionary, the target service data packet, a first knowledge base and a second knowledge base into a preset large model, and outputting a question and answer result based on the preset large model, wherein the first knowledge base is a basic knowledge base related to the text information input by the user, and the second knowledge base is a similar knowledge base related to the text information input by the user. By adopting the technical scheme, the service data information can be queried in real time, and the response speed of the service data information and the accuracy of response content are improved.
Fig. 2a shows a flowchart of a question and answer result output method according to an embodiment of the present disclosure. Embodiments of the present disclosure may be optimized based on the embodiments described above, and may be combined with various alternatives of one or more of the embodiments described above.
As shown in fig. 2a, the question and answer result output method may include the steps of:
S201, acquiring text information input by a user, and determining an initial service data packet according to the text information input by the user, wherein the initial service data packet is used for representing service data information associated with the text information input by the user.
In one example, determining an initial service data packet based on text information entered by a user includes:
Inputting text information input by a user into a classification model, and determining the business category to which the text information input by the user belongs based on the classification model;
and identifying keywords in text information input by a user based on the classification model, and determining an initial service data packet in the service category according to the keywords.
In one example, the classification model is used to make business class determinations for text information entered by a user. In this embodiment, different service data information belongs to different service classes, and the same service class includes a plurality of different initial service data packets.
In this embodiment, after determining, through the classification model, the service class to which the text information input by the user belongs, and then determining, in the service class, the initial service data packet associated with the text information input by the user through the keyword in the text information input by the user.
S202, acquiring a preset semantic mapping dictionary and an index dictionary.
In one example, this step may be referred to the content of step S102.
S203, performing first conversion processing on the initial service data packet according to a preset semantic mapping dictionary to obtain an intermediate service data packet.
In one example, performing a first conversion process on an initial service data packet according to a preset semantic mapping dictionary to obtain an intermediate service data packet, including:
Acquiring first semantic information and second semantic information in a preset semantic mapping dictionary, and searching the first semantic information in an initial service data packet, wherein the first semantic information and the second semantic information have a corresponding relation;
And replacing the first semantic information in the initial service data packet with the second semantic information to obtain an intermediate service data packet.
In one example, the first semantic information may be english semantic information and the second semantic information may be chinese semantic information. Specifically, the preset semantic mapping dictionary may be:
{
"name"; "name",
"Phone"; "phone",
"Sex"; "gender",
}
Wherein, "name", "phone", "sex" is first semantic information, and "name", "phone", "sex" is second semantic information.
In one example, the initial traffic data packet may be:
{
"name"; "Zhang san",
“phone”;“123456789”,
"Sex"; "man",
}
Wherein, "name", "phone", "sex" is the first semantic information. In this embodiment, the first semantic information "name" is found in the initial service data packet, then the first semantic information "name" is replaced with the second semantic information "name" in the initial service data packet, and other first semantic information is also replaced, so that the intermediate service data packet may be:
{
"name"; "Zhang san",
"Telephone"; "123456789",
"Sex"; "man",
}
Specifically, the english semantic information in the intermediate service data packet has been replaced with chinese semantic information.
S204, performing second conversion processing on the intermediate service data packet according to the index dictionary to obtain a target service data packet.
In one example, performing a second conversion process on the intermediate service data packet according to the index dictionary to obtain a target service data packet, including:
Acquiring second semantic information and numbering information in an index dictionary, and searching the second semantic information in an intermediate service data packet, wherein the second semantic information and the numbering information have a corresponding relation;
And replacing the second semantic information in the intermediate service data packet with the number information to obtain the target service data packet.
In one example, the numbering information is digital information, which may be 1,2, or 3, for example.
In this embodiment, the index dictionary may be:
{
"name"; "1",
"Telephone"; "2",
"Sex"; "3",
}
In one example, the second semantic information "name" is searched in the intermediate service data packet, the "name" is replaced by the number information "1", and other second semantic information is also replaced, so that the target service data packet is obtained:
{
"1"; "Zhang san",
“2”;“123456789”,
"3"; "Man",
}
Specifically, the chinese semantic information in the target service data packet has been replaced with numbering information. The advantage of this arrangement is that the cost of use of the pre-set large model can be effectively reduced.
S205, inputting text information input by a user, an index dictionary, a target business data packet, a first knowledge base and a second knowledge base into a preset large model, and outputting a question-answer result based on the preset large model, wherein the first knowledge base is a basic knowledge base associated with the text information input by the user, and the second knowledge base is a similar knowledge base associated with the text information input by the user.
In one example, the second knowledge base is a similar knowledge base associated with text information entered by a user, comprising:
Inputting text information input by a user into an expansion knowledge base, and searching text information similar to the text information input by the user in the expansion knowledge base;
And determining the similar text information as a second knowledge base.
In one example, the step may be parallel processed with step S201, specifically, the text information input by the user is expanded in the expansion knowledge base, so that more service data information related to the text information input by the user can be obtained, and then the second knowledge base is obtained.
In one example, determining similar text information as the second knowledge base includes:
and combining the similar text information which is larger than the threshold value to obtain a second knowledge base.
In one example, the threshold may be set in advance. In this embodiment, based on a preset similarity algorithm, similar text information greater than a threshold may be found, and all similar text information greater than the threshold may be combined to obtain a second knowledge base.
For a clearer illustration, reference may be made to a schematic illustration of a question and answer result output process shown in fig. 2 b.
The embodiment of the disclosure provides a question and answer result output method, which comprises the steps of obtaining text information input by a user, determining an initial service data packet according to the text information input by the user, obtaining a preset semantic mapping dictionary and an index dictionary, performing first conversion processing on the initial service data packet according to the preset semantic mapping dictionary to obtain a middle service data packet, and performing second conversion processing on the middle service data packet according to the index dictionary to obtain a target service data packet. Inputting text information input by a user, an index dictionary, a target service data packet, a first knowledge base and a second knowledge base into a preset large model, and outputting a question-answer result based on the preset large model, wherein the first knowledge base is a basic knowledge base associated with the text information input by the user, and the second knowledge base is a similar knowledge base associated with the text information input by the user. By adopting the technical scheme, the use cost of the large model is reduced, and the desensitization processing of the data is realized through simple field configuration.
Fig. 3 is a schematic structural diagram of a question-answer result output apparatus provided in an embodiment of the present disclosure, where the question-answer result output apparatus may be understood as the above-mentioned electronic device or a part of functional modules in the above-mentioned electronic device. As shown in fig. 3, the question-answer result output means 30 includes:
the acquiring module 301 is configured to acquire text information input by a user, and determine an initial service data packet according to the text information input by the user, where the initial service data packet is used to characterize service data information associated with the text information input by the user.
The processing module 302 is configured to obtain a preset semantic mapping dictionary and an index dictionary, and perform conversion processing on the initial service data packet according to the preset semantic mapping dictionary and the index dictionary to obtain a target service data packet.
The output module 303 is configured to input text information input by a user, an index dictionary, a target service data packet, a first knowledge base and a second knowledge base into a preset big model, and output a question-answer result based on the preset big model, where the first knowledge base is a basic knowledge base associated with the text information input by the user, and the second knowledge base is a similar knowledge base associated with the text information input by the user.
In one example, the processing module 302 includes:
the first processing sub-module is used for performing first conversion processing on the initial service data packet according to a preset semantic mapping dictionary to obtain an intermediate service data packet;
and the second processing sub-module is used for carrying out second conversion processing on the intermediate service data packet according to the index dictionary to obtain the target service data packet.
In one example, the first processing sub-module is specifically configured to:
Acquiring first semantic information and second semantic information in a preset semantic mapping dictionary, and searching the first semantic information in an initial service data packet, wherein the first semantic information and the second semantic information have a corresponding relation;
And replacing the first semantic information in the initial service data packet with the second semantic information to obtain an intermediate service data packet.
In one example, the second processing sub-module is specifically configured to:
Acquiring second semantic information and numbering information in an index dictionary, and searching the second semantic information in an intermediate service data packet, wherein the second semantic information and the numbering information have a corresponding relation;
And replacing the second semantic information in the intermediate service data packet with the number information to obtain the target service data packet.
In one example, the acquisition module 301 includes:
The first determining submodule is used for inputting text information input by a user into the classification model and determining the service class to which the text information input by the user belongs based on the classification model;
And the second determining sub-module is used for identifying keywords in text information input by a user based on the classification model and determining initial service data packets in service categories according to the keywords.
In one example, the second knowledge base is a similar knowledge base associated with text information entered by a user, comprising:
Inputting text information input by a user into an expansion knowledge base, and searching text information similar to the text information input by the user in the expansion knowledge base;
And determining the similar text information as a second knowledge base.
In one example, determining similar text information as the second knowledge base includes:
and combining the similar text information which is larger than the threshold value to obtain a second knowledge base.
The device provided in this embodiment can execute the method of any one of the above embodiments, and the execution mode and the beneficial effects thereof are similar, and are not described herein again.
The embodiment of the disclosure also provides electronic equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor is used for executing the computer program, and the method of any embodiment can be realized when the computer program is executed by the processor.
By way of example, fig. 4 is a schematic structural diagram of an electronic device in an embodiment of the present disclosure. Referring now in particular to fig. 4, a schematic diagram of an electronic device 1000 suitable for use in implementing embodiments of the present disclosure is shown. The electronic device 1000 in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 4 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
As shown in fig. 4, the electronic device 1000 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 1001 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 1002 or a program loaded from a storage means 1008 into a Random Access Memory (RAM) 1003. In the RAM 1003, various programs and data necessary for the operation of the electronic apparatus 1000 are also stored. The processing device 1001, the ROM 1002, and the RAM 1003 are connected to each other by a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.
In general, devices including input devices 1006 such as a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc., output devices 1007 including a Liquid Crystal Display (LCD), speaker, vibrator, etc., storage devices 1008 including, for example, magnetic tape, hard disk, etc., and communication devices 1009 may be connected to the I/O interface 1005. The communication means 1009 may allow the electronic device 1000 to communicate wirelessly or by wire with other devices to exchange data. While fig. 4 shows an electronic device 1000 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs.
A fifth aspect of the disclosed embodiments provides a computer program product comprising a computer program which, when executed by a processor, implements a method as in the first aspect.
In such an embodiment, the computer program may be downloaded and installed from a network via the communication device 1009, or installed from the storage device 1008, or installed from the ROM 1002. The above-described functions defined in the method of the embodiment of the present disclosure are performed when the computer program is executed by the processing device 1001.
It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to electrical wiring, fiber optic cable, RF (radio frequency), and the like, or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.
The computer readable medium may be included in the electronic device or may exist alone without being incorporated into the electronic device.
The computer readable medium carries one or more programs, when the one or more programs are executed by the electronic equipment, the electronic equipment is caused to acquire text information input by a user, determine an initial business data packet according to the text information input by the user, wherein the initial business data packet is used for representing business data information related to the text information input by the user, acquire a preset semantic mapping dictionary and an index dictionary, convert the initial business data packet according to the preset semantic mapping dictionary and the index dictionary to obtain a target business data packet, input the text information input by the user, the target business data packet, a first knowledge base and a second knowledge base into a preset large model, output a question-answer result based on the preset large model, and the first knowledge base is a basic knowledge base related to the text information input by the user, and the second knowledge base is a similar knowledge base related to the text information input by the user. Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic that may be used include Field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems-on-a-chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The embodiments of the present disclosure further provide a computer readable storage medium, where a computer program is stored, where when the computer program is executed by a processor, the method of any of the foregoing embodiments may be implemented, and the implementation manner and the beneficial effects are similar, and are not repeated herein.
It should be noted that in this document, 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 above is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. 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 disclosure. Thus, the present disclosure 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.