CN110349008B - Decision support method and device based on natural language and electronic equipment - Google Patents
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Abstract
The invention discloses a decision support method, a device, electronic equipment and a computer readable medium based on natural language. The method first receives business rule configuration information described by natural language, then identifies the natural language to obtain the business rule configuration information, and determines a business strategy based on the business rule configuration information. The invention separates the business decision from the program code, supports the writing of the business rule by using the predefined natural language, is convenient for business rule maintainers and decision makers to operate and maintain the business, and improves the decision making efficiency.
Description
Technical Field
The present invention relates to the field of computer information processing, and in particular, to a decision support method, apparatus, electronic device and computer readable medium based on natural language.
Background
Since the 21 st century, there has been a great change in how administrators employ computerized support in the decision-making process. As more and more decision makers master computer and Web knowledge, decision support systems/business intelligence are evolving continuously, and from the beginning as a basic personal support tool, is rapidly becoming a commonplace in the whole organization. The data warehouse and analysis tools greatly enhance the retrieval of information across institutional limits. Decision support provided for teams continues to improve with the new development of group support systems to improve collaborative work at any time and any place.
Artificial intelligence methods are improving the quality of decision support and have penetrated many application areas. Intelligent agents perform conventional tasks, enabling decision makers to spend more time focusing on important tasks, and the development of organized learning and knowledge management makes it possible to provide the entire institution's expertise for the problem at any time and place.
Internet and intranet information delivery systems have improved and facilitated all of these decision support systems. Compared with the traditional industry, the Internet industry requires higher timeliness and higher flexibility, and the traditional decision engine system is poor in recoding and readability and deployment timeliness. Therefore, a decision support system that is convenient for decision-making personnel to operate and improves decision-making efficiency is highly desirable.
Disclosure of Invention
In view of the foregoing, the present invention provides a natural language based decision support method, apparatus, electronic device, and computer readable medium that overcomes or at least partially solves the foregoing problems.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
In a first aspect, the present invention provides a decision support method based on natural language, including the steps of:
receiving service rule configuration information described by natural language;
identifying the natural language to obtain the business rule configuration information;
and determining a service policy based on the service rule configuration information.
According to a preferred embodiment of the present invention, the receiving the business rule configuration information described using natural language further includes:
listing a recommended parameter information list of the service rule according to the historical service rule data, wherein the recommended parameter information comprises a parameter name, a parameter optimization range and a parameter optimization logic relationship;
and receiving selection of at least one of a parameter name, a parameter preference range and a parameter preference logic relation of at least one parameter in the recommended parameter list.
According to a preferred embodiment of the invention, the parameters of the business rule configuration comprise variables and/or constants.
According to a preferred embodiment of the present invention, the service rule configuration information includes rule combination package information, and the rule combination package includes configuration information of a plurality of rules and a logical relationship between the rules.
According to a preferred embodiment of the present invention, determining a service policy based on the service rule configuration information comprises:
analyzing the logic relation before each rule in the rule combination package;
and obtaining a service strategy based on the analysis result of the rule combination package.
According to a preferred embodiment of the present invention, the parsing the rules and the logical relationship before the rules in the rule combination package includes: the rule combination package is parsed by a Drools rule engine.
According to a preferred embodiment of the invention, the business rules comprise at least one of the following, or any combination thereof:
parameter management rules, policy management rules, flow management rules, deployment management rules.
A second aspect of the present invention proposes a decision support apparatus based on natural language, comprising: the receiving module is used for receiving the business rule configuration information described by using natural language; the identification module is used for identifying the natural language to obtain the business rule configuration information; and the determining module is used for determining the service policy based on the service rule configuration information.
According to a preferred embodiment of the present invention, the receiving module further comprises:
the recommendation module is used for listing a recommendation parameter information list of the service rule according to the historical service rule data, wherein the recommendation parameter information comprises a parameter name, a parameter optimization range and a parameter optimization logic relationship;
and the selection module is used for receiving the selection of at least one of the parameter name, the parameter preference range and the parameter preference logic relation of at least one parameter in the recommended parameter list.
According to a preferred embodiment of the invention, the parameters of the business rule configuration comprise variables and/or constants.
According to a preferred embodiment of the present invention, the service rule configuration information includes rule combination package information, and the rule combination package includes configuration information of a plurality of rules and a logical relationship between the rules.
According to a preferred embodiment of the present invention, the parsing module is configured to parse each rule and a logical relationship before the rule in the rule combination package; and the policy module is used for obtaining the service policy based on the analysis result of the rule combination package.
According to a preferred embodiment of the invention, the parsing module processes the rule combination package through a Drools rule engine.
According to a preferred embodiment of the invention, the business rules comprise at least one of the following, or any combination thereof: parameter management rules, policy management rules, flow management rules, deployment management rules.
In a third aspect, the present description provides a server comprising a processor and a memory:
the memory is used for storing a program for executing the method of any one of the above;
the processor is configured to execute a program stored in the memory.
In a fourth aspect, embodiments of the present invention provide a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of any of the methods described above.
The invention separates business decision from program codes, supports writing business rules by using predefined natural language, is convenient for business rule maintainers and decision makers to operate and maintain business, and improves decision making efficiency.
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In order to make the technical problems solved by the present invention, the technical means adopted and the technical effects achieved more clear, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted, however, that the drawings described below are merely illustrative of exemplary embodiments of the present invention and that other embodiments of the present invention may be derived from these drawings by those skilled in the art without undue effort.
FIG. 1 is a flowchart of a natural language based decision support method according to an exemplary embodiment of the invention;
fig. 2 is a block diagram of a natural language based decision support apparatus according to another exemplary embodiment of the present invention.
Fig. 3 is a schematic structural diagram of an embodiment of an electronic device according to the present invention;
fig. 4 is a schematic structural diagram of a computer readable medium according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals in the drawings denote the same or similar elements, components or portions, and thus a repetitive description thereof will be omitted.
The features, structures, characteristics or other details described in a particular embodiment do not exclude that may be combined in one or more other embodiments in a suitable manner, without departing from the technical idea of the invention.
In the description of specific embodiments, features, structures, characteristics, or other details described in the present invention are provided to enable one skilled in the art to fully understand the embodiments. However, it is not excluded that one skilled in the art may practice the present invention without one or more of the specific features, structures, characteristics, or other details.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various devices, elements, components or portions, this should not be limited by these terms. These words are used to distinguish one from the other. For example, a first device may also be referred to as a second device without departing from the spirit of the invention.
The term "and/or" and/or "includes all combinations of any of the associated listed items and one or more.
In view of the problems of the prior art, the invention provides a decision support method and a corresponding device based on natural language. In a specific embodiment, the method and apparatus are implemented based on a customized rules engine of the open source rules engine tool, drools. Thus, the present invention enables the separation of business decisions from program code and supports the writing of business rules in predefined natural language.
In general, the invention accepts data input in natural language, parses business rules, and determines business policies based on the business rules. The method specifically comprises the following steps: receiving service rule configuration information described by natural language; identifying the natural language to obtain the business rule configuration information; and determining a service policy based on the service rule configuration information.
The system accepts data input, interprets business rules, and makes business decisions according to the business rules.
The technical scheme of the invention is described and illustrated in detail through specific embodiments.
Fig. 1 is a flowchart of a natural language based decision support method according to an exemplary embodiment of the present invention. This embodiment is based on the customized rules engine system of open source rules engine tool-Drools, which enables the separation of business decisions from program code and supports the writing of business decisions using predefined natural language modules. Referring to fig. 1, the natural language based decision support method includes:
s101: business rule configuration information described using natural language is received.
This step may provide a user interaction interface for natural language authoring of business rules, including display means and input means.
According to a preferred embodiment of the present invention, upon receiving service rule configuration information described in natural language, a recommended parameter information list of the service rule is provided, the recommended parameter information including a parameter name, a parameter preference range, and a parameter preference logical relationship.
For financial services, a rule is often formulated with a large number of parameters, each of which may be of a different type and range of values, discrete and continuous. For example, for an age parameter, it is a continuous number, but the number actually used in the rule may be concentrated in a certain section. For another example, it is a discrete parameter that may be required to work together with other parameters in a rule, such as "1000 yuan raised for men older than 27 years old".
Policies for different types of services, including credit, anti-fraud, credit, rating, revenue, etc., are also quite different as to the parameters used by the rules of the service. It is sometimes difficult for an operator who needs to handle numerous services to make meaningful selections from among numerous parameters. Therefore, a machine self-learning mode is adopted to provide a recommended parameter information list, so that operation and maintenance personnel can conveniently and quickly select proper parameters while making strategies through natural language.
Of course, the present invention is not limited to directly generating rules, and can assist in generating rules by techniques such as computer or artificial intelligence based on conventional experience in formulating rules.
In order to provide the recommended parameter information list more accurately, the embodiment of the invention establishes a history service rule base, records the history use rules and the use frequency thereof, and marks the rules according to the rule types. In addition, the rules can be scored and recorded according to the actual utility of the historical business rules. According to the historical business rule data, the information such as parameters used by higher frequencies in different business rules, ranges of the parameters, logical relations among the parameters and the like can be listed through some statistical algorithms.
More preferably, the invention can be derived from learning parameters and parameter values that perform better by building a machine learning model (the greater the effect on the final scoring of the rules is). The IV value may be used to calculate important parameters, for example.
When a list of information for recommending parameters is provided, in this embodiment, a selection of at least one of a parameter name, a parameter preference range and a parameter preference logical relationship of at least one parameter in the list of recommended parameters is received in a visual manner in a user interaction interface. Therefore, the user can quickly select the rule parameters and parameter values which the user wants to make the business rule.
S102: and identifying the natural language to obtain the business rule configuration information.
This step identifies the natural language used to configure the business rules on the user interaction interface. The identifying process includes identifying natural language for configuring the business rule parameters, the parameters including variables or constants.
S103: and determining a service policy based on the service rule configuration information.
This step is used to generate a business strategy that is directly available to the computer. However, many times a policy often requires multiple rules. Therefore, preferably, the service rule configuration information includes rule combination package information, and the rule combination package includes configuration information of a plurality of rules and logic relations among the rules. And the business rules include one or more combinations of the following: parameter management rules, policy management rules, flow management rules, deployment management rules;
in this embodiment, the rule combination package is processed by a Drools rule engine, and a service policy is obtained based on the processing result of the rule combination package.
The method ensures that the invention achieves the following technical effects:
(1) The natural language, namely the code mode (if, not) in the rule writing process is changed into the natural language (if, then) and is used for configuring an interface to enable operators and strategic personnel to deploy, so that the rule package is deployed from tens of minutes to minutes, and the timeliness is higher.
(2) The method is characterized in that the strategy is automatically translated into a combination package of various rules, the number of the rules is more than twenty thousand, a rule name, a code number and four parameters are arranged in one rule, the parameters have an execution sequence, the four parameters such as the when and the then are corresponding to one code view, and parameter variables/constants in the rules can be selected according to the requirements of operators, so that the readability is higher.
(3) The invention divides the business rule writing into parameter management/strategy management/flow management/deployment management. Parameter management corresponds to input and output of bottom data, supports pre-configuration and various types of data application, and is a precondition for realizing configuration of a decision engine. Policy management, i.e. the application place where the rule engine implements various scene policies, each policy corresponds to an application scene, and each policy contains a plurality of different decision conditions in the scene. The flow management, namely the production flow corresponding to the business logic, is the key point of the decision-to-decision flow. Deployment management is a standardized policy online flow, and strict authority management is corresponding to the back of the policy online flow, so that policy security is the final guarantee of online.
Those skilled in the art will appreciate that all or part of the steps implementing the above-described embodiments are implemented as a program (computer program) executed by a computer data processing apparatus. The above-described method provided by the present invention can be implemented when the computer program is executed. Moreover, the computer program may be stored in a computer readable storage medium, which may be a readable storage medium such as a magnetic disk, an optical disk, a ROM, a RAM, or a storage array composed of a plurality of storage media, for example, a magnetic disk or a tape storage array. The storage medium is not limited to a centralized storage, but may be a distributed storage, such as cloud storage based on cloud computing.
The following describes apparatus embodiments of the invention that may be used to perform method embodiments of the invention. Details described in the embodiments of the device according to the invention should be regarded as additions to the embodiments of the method described above; for details not disclosed in the embodiments of the device according to the invention, reference may be made to the above-described method embodiments.
Fig. 2 is a block diagram of a natural language based decision support apparatus according to another exemplary embodiment of the present invention. As shown in fig. 2, the apparatus includes a receiving module, an identifying module, and a determining module.
The receiving module is used for receiving the business rule configuration information described by using natural language;
the receiving module can be used for compiling business rules in natural language by means of a user interaction interface, and comprises a display device and an input device.
According to a preferred embodiment of the present invention, when receiving service rule configuration information described in natural language, the receiving module further includes a recommending module, and provides a recommended parameter information list of the service rule, where the recommended parameter information includes a parameter name, a parameter preferred range, and a parameter preferred logic relationship.
For financial services, a rule is often formulated with a large number of parameters, each of which may be of a different type and range of values, discrete and continuous. For example, for an age parameter, it is a continuous number, but the number actually used in the rule may be concentrated in a certain section. For another example, it is a discrete parameter that may be required to work together with other parameters in a rule, such as "1000 yuan raised for men older than 27 years old".
Policies for different types of services, including credit, anti-fraud, credit, rating, revenue, etc., are also quite different as to the parameters used by the rules of the service. It is sometimes difficult for an operator who needs to handle numerous services to make meaningful selections from among numerous parameters. Therefore, a machine self-learning mode is adopted to provide a recommended parameter information list, so that operation and maintenance personnel can conveniently and quickly select proper parameters while making strategies through natural language.
Of course, the present invention is not limited to directly generating rules, and can assist in generating rules by techniques such as computer or artificial intelligence based on conventional experience in formulating rules.
In order to provide the recommended parameter information list more accurately, the embodiment of the invention establishes a history service rule base, records the history use rules and the use frequency thereof, and marks the rules according to the rule types. In addition, the rules can be scored and recorded according to the actual utility of the historical business rules. According to the historical business rule data, the information such as parameters used by higher frequencies in different business rules, ranges of the parameters, logical relations among the parameters and the like can be listed through some statistical algorithms.
More preferably, the invention can be derived from learning parameters and parameter values that perform better by building a machine learning model (the greater the effect on the final scoring of the rules is). The IV value may be used to calculate important parameters, for example.
The receiving module further comprises a selection module, and when the recommending module provides the information list for recommending the parameters, the selection module receives selection of at least one of the parameter names, the parameter optimization ranges and the parameter optimization logic relations of at least one parameter in the recommended parameter list in a visual mode through a user interaction interface. Therefore, the user can quickly select the rule parameters and parameter values which the user wants to make the business rule.
The identification module is used for identifying the natural language to obtain the business rule configuration information. The module identifies natural language used to configure the business rules on the user interaction interface. The identifying process includes identifying natural language for configuring the business rule parameters, the parameters including variables or constants.
And the determining module is used for determining the service policy based on the service rule configuration information. The module is used to generate business policies that are directly available to the computer. However, many times a policy often requires multiple rules. Therefore, preferably, the service rule configuration information includes rule combination package information, and the rule combination package includes configuration information of a plurality of rules and logic relations among the rules. And the business rules include one or more combinations of the following: parameter management rules, policy management rules, flow management rules, deployment management rules;
in this embodiment, the rule combination package is processed by a Drools rule engine, and a service policy is obtained based on the processing result of the rule combination package.
It will be appreciated by those skilled in the art that the modules in the embodiments of the apparatus described above may be distributed in an apparatus as described, or may be distributed in one or more apparatuses different from the embodiments described above with corresponding changes. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.
The following describes an embodiment of an electronic device according to the present invention, which may be regarded as a specific physical implementation of the above-described embodiment of the method and apparatus according to the present invention. Details described in relation to the embodiments of the electronic device of the present invention should be considered as additions to the embodiments of the method or apparatus described above; for details not disclosed in the embodiments of the electronic device of the present invention, reference may be made to the above-described method or apparatus embodiments.
Fig. 3 is a block diagram of an exemplary embodiment of an electronic device according to the present invention. An electronic device 300 according to this embodiment of the present invention is described below with reference to fig. 3. The electronic device 300 shown in fig. 3 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 3, the electronic device 300 is embodied in the form of a general purpose computing device. Components of electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one memory unit 320, a bus 330 connecting the different system components (including the memory unit 320 and the processing unit 310), a display unit 340, and the like.
Wherein the storage unit stores program code that is executable by the processing unit 310 such that the processing unit 310 performs the steps according to various exemplary embodiments of the present invention described in the electronic prescription stream processing method section above in this specification. For example, the processing unit 310 may perform the steps shown in fig. 3.
The memory unit 320 may include readable media in the form of volatile memory units, such as Random Access Memory (RAM) 3201 and/or cache memory 3202, and may further include Read Only Memory (ROM) 3203.
The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
Bus 330 may be one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 300 may also communicate with one or more external devices 400 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 300, and/or any device (e.g., router, modem, etc.) that enables the electronic device 300 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 350. Also, electronic device 300 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 360. The network adapter 360 may communicate with other modules of the electronic device 300 via the bus 330. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 300, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the exemplary embodiments described herein may be implemented in software, or may be implemented in software in combination with necessary hardware. Thus, the technical solution according to the embodiments of the present invention may be embodied in the form of a software product, which may be stored in a computer readable storage medium (may be a CD-ROM, a usb disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, or a network device, etc.) to perform the above-mentioned method according to the present invention. The computer program, when executed by a data processing device, enables the computer readable medium to carry out the above-described method of the present invention, namely:
the invention utilizes a large amount of user information stored in a company database to construct time series data of user operation, and accordingly, a risk prediction model is established to predict the possibility of overdue, fake and intermediation of the user. Different coping strategies are implemented for different model prediction results, so that the risk of a user can be identified more accurately, more unknown risks can be found by utilizing manual assistance to explore, the model is fed back, and the prediction accuracy is improved.
Fig. 4 is a schematic diagram of a computer readable medium according to the present invention.
The computer program may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is 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 (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with 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 readable storage medium may also be any readable medium 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 readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like 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 computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in accordance with embodiments of the present invention may be implemented in practice using a general purpose data processing device such as a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
The above-described specific embodiments further describe the objects, technical solutions and advantageous effects of the present invention in detail, and it should be understood that the present invention is not inherently related to any particular computer, virtual device or electronic apparatus, and various general-purpose devices may also implement the present invention. The foregoing description of the embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (8)
1. A natural language-based decision support method, comprising the steps of:
providing a list of recommended parameter information of a business rule, receiving business rule configuration information described by natural language, comprising: establishing a historical service rule base, recording service rules used in history and the use frequency thereof, marking according to rule types, and grading and recording the rules according to the actual utility of the historical service rules; listing the logic relation between parameters used by high frequency in different business rules and parameter ranges and parameters according to historical business rule data by a statistical algorithm; determining recommended parameter information by establishing a machine learning model from the well-represented parameters and parameter values in the learning rule, listing a list of recommended parameter information of the service rule, and receiving selection of at least one of a parameter name, a parameter optimization range and a parameter optimization logic relationship of at least one parameter in the list of recommended parameter information in a visual manner at a user interaction interface to obtain service rule configuration information described by using natural language; the recommended parameter information comprises a parameter name, a parameter optimization range and a parameter optimization logic relationship;
identifying the natural language configuring the business rule parameters on a user interaction interface to obtain the business rule configuration information; wherein the business rule configuration information comprises a rule combination packet;
determining a business policy based on the business rule configuration information comprises: analyzing the logic relation among all rules in the rule combination package; and obtaining the service strategy based on the analysis result of the rule combination package.
2. The method of claim 1, wherein the identifying parameters in the natural language configuring the business rule parameters comprises: variable and/or constant.
3. The method of claim 1, wherein the rule combination package comprises: configuration information of a plurality of rules and logic relations among the rules.
4. The method of claim 1, wherein said parsing each rule and logical relationships between rules within the rule-combination package comprises: the rule combination package is parsed by a Drools rule engine.
5. The method of claim 1, wherein the business rules comprise at least one of the following, or any combination thereof:
parameter management rules, policy management rules, flow management rules, deployment management rules.
6. A natural language based decision support apparatus comprising:
the receiving module is configured to provide a list of recommended parameter information of the service rule, and receive service rule configuration information described by using natural language, and includes: establishing a historical service rule base, recording service rules used in history and the use frequency thereof, marking according to rule types, and grading and recording the rules according to the actual utility of the historical service rules; listing the logic relation between parameters used by high frequency in different business rules and parameter ranges and parameters according to historical business rule data by a statistical algorithm; determining recommended parameter information by establishing a machine learning model from the well-represented parameters and parameter values in the learning rule, listing a list of recommended parameter information of the service rule, and receiving selection of at least one of a parameter name, a parameter optimization range and a parameter optimization logic relationship of at least one parameter in the list of recommended parameter information in a visual manner at a user interaction interface to obtain service rule configuration information described by using natural language; the recommended parameter information comprises a parameter name, a parameter optimization range and a parameter optimization logic relationship;
the identification module is used for identifying the natural language configuring the business rule parameters on a user interaction interface so as to obtain the business rule configuration information; wherein the business rule configuration information comprises a rule combination packet;
the determining module, configured to determine a service policy based on the service rule configuration information includes: analyzing the logic relation among all rules in the rule combination package; and obtaining the service strategy based on the analysis result of the rule combination package.
7. A server comprising a processor and a memory:
the memory is used for storing a program for executing the method of any one of claims 1 to 5;
the processor is configured to execute a program stored in the memory.
8. A computer readable storage medium storing a computer program, characterized in that the program when executed by a processor implements the steps of the method according to any one of claims 1 to 5.
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| CN110782232A (en) * | 2019-11-04 | 2020-02-11 | 北京明略软件系统有限公司 | Business process visual configuration method and device, electronic equipment and storage medium |
| CN113010231A (en) * | 2021-03-29 | 2021-06-22 | 上海寻梦信息技术有限公司 | Rule configuration method, device and equipment for logistics aging prediction and storage medium |
| CN113380354B (en) * | 2021-06-16 | 2024-05-24 | 联仁健康医疗大数据科技股份有限公司 | Personnel recruitment method, device, system, electronic equipment and storage medium |
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