CN113254061B - Business decision method, system and storage medium based on rule engine - Google Patents
Business decision method, system and storage medium based on rule engine Download PDFInfo
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Abstract
The invention discloses a business decision method, a system and a storage medium based on a rule engine, wherein the method comprises the following steps: the rule configuration server deploys service configuration rule information in real time according to a rule strategy set pre-configured by a service party, stores the service configuration rule information to a database, independently simulates and tests different resources aiming at the different resources, outputs a result, and sends the service configuration rule information to the rule execution server; and the rule execution server executes a corresponding strategy according to the model data sent by the service calling party and the service configuration rule information, and outputs a decision result. The invention can get rid of the great dependence of the traditional operation decision on business personnel and IT personnel, reduce the enterprise cost, reduce the learning cost of a decision engine system, realize the real simplicity, rapidness and easy operation, shorten the strategy release period and deal with the environmental change in real time.
Description
Technical Field
The invention relates to the technical field of rule engines, in particular to a business decision method, a business decision system and a storage medium based on a rule engine.
Background
The rule engine is developed by an inference engine, is a component embedded in an application program, and realizes the separation of business decisions from application program codes and the writing of the business decisions by using a predefined semantic module. And receiving data input, interpreting business rules, and making business decisions according to the business rules.
In the prior art, a rule configuration server configures a data model of a corresponding business party, abstracts resources corresponding to different scenes, such as a rule set, a single-axis decision table, a double-axis decision table, a function, a score card and the like, and uses a decision flow to connect all the resources in series to form a rule execution whole.
At present, a complete decision needs a complex human review process, decision periods are uneven, and enterprises are difficult to bear more services under limited resources. The human review process needs to invest a large number of high-quality personnel to ensure the timeliness and accuracy of the approval, and business loss is easily caused due to insufficient personnel and errors of decision making by subjective experience and the like. And because the policy and the market environment change instantly, the response is not timely, and the policy adjustment is delayed. The business personnel and IT personnel are mixed to develop a rule form, a private black box environment cannot be provided for the wind control technology, and the leakage risk exists.
Disclosure of Invention
The invention mainly aims to provide a business decision method, a business decision system and a storage medium based on a rule engine, which aims to get rid of the great dependence of the traditional business decision on business personnel and IT personnel, reduce the enterprise cost, reduce the learning cost of a decision engine system, realize the real simplicity, quickness and easiness in operation, shorten the strategy release period and deal with the environmental change in real time.
In order to achieve the above object, the present invention provides a business decision method based on a rule engine, which is applied to a business decision system of the rule engine, wherein the system comprises a rule configuration server and a rule execution server, and the method comprises the following steps:
the rule configuration server deploys service configuration rule information in real time in a preset mode according to a rule strategy set pre-configured by a service party, stores the service configuration rule information into a database, independently simulates and tests different resources aiming at the different resources, outputs a result, and sends the service configuration rule information to a rule execution server;
and the rule execution server executes a corresponding strategy according to the model data sent by the service calling party and the service configuration rule information, and outputs a decision result.
The further technical scheme of the invention is that the step of independently testing different resources aiming at different resources and outputting results comprises the following steps:
and calculating and matching the input data by adopting a RETE algorithm of a rule engine and outputting a result.
The invention further adopts the technical scheme that when the RETE algorithm is used for carrying out mode matching, the mode matching is carried out according to the generated authentication network, the types of non-root nodes in the network comprise 1-input nodes and 2-input nodes, the 1-input nodes form an Alpha network, and the 2-input nodes form a Beta network.
The further technical scheme of the invention is that the step of calculating, matching and outputting the result to the input data by adopting the RETE algorithm of the rule engine comprises the following steps:
match: finding out a work memory set conforming to the LHS part;
confilict resolution: selecting a rule for which a condition is satisfied;
act: content to perform RHS;
and returning to the Match step.
The further technical scheme of the invention is that the step of deploying the service configuration rule information in real time by the rule configuration server side in a preset mode according to the rule strategy set pre-configured by the service party comprises the following steps:
and the rule configuration server deploys the service configuration rule information in real time in an HTTP mode according to a rule strategy set pre-configured by a service party.
The further technical scheme of the invention is that the step that the rule configuration server deploys the service configuration rule information in real time in a preset mode according to the rule strategy set pre-configured by the service party and sends the service configuration rule information to the rule execution server comprises the following steps:
the rule configuration server deploys service configuration rule information in real time in a preset mode according to a rule strategy set pre-configured by a service party, generates DRL files conforming to the specifications of a Drools rule engine according to the service configuration rule information, and issues rule operation files to the rule execution server.
The further technical scheme of the invention is that the step of deploying the service configuration rule information in real time by the rule configuration server side in a preset mode according to the rule strategy set pre-configured by the service party comprises the following steps:
and pre-configuring a rule strategy set, wherein the rule strategy set is a set of resources required by rule operation, defining the strategy set name, adding resource information after selecting a data model, and the resource information type comprises a strategy main flow, a rule set, a score card, a sub-decision flow, a programmable function, a hard coding function, a single-axis decision table and a double-axis decision table.
The invention has the further technical scheme that one rule strategy set has only one strategy main flow, the nodes of the strategy main flow can select start, finish, the rule set, the score card, the programmable function, the hard coding function, the single-axis decision table, the double-axis decision table and the like, resources are connected into a flow chart through gateway connecting lines, and the flow nodes execute related instructions according to the sequence of the flow chart.
In order to achieve the above object, the present invention further provides a business decision system based on a rule engine, where the system includes a rule configuration server, a rule execution server, a memory, and a processor, where the memory stores a business decision program based on the rule engine, and the business decision program based on the rule engine executes the steps of the method when called by the processor.
To achieve the above object, the present invention further provides a computer readable storage medium, which stores a rule engine based business decision program, and when the rule engine based business decision program is called by a processor, the rule engine based business decision program executes the steps of the method as described above.
The business decision method, the system and the storage medium based on the rule engine have the advantages that: according to the technical scheme, the method and the system can get rid of the great dependence of the traditional operation decision on business personnel and IT personnel, reduce the enterprise cost, reduce the learning cost of a decision engine system, realize the real simplicity, rapidness and easiness in operation, shorten the strategy release period, deal with the environmental change in real time, make the risk data return on the ground, serve the risk policy and make more enterprises depending on the traditional decision mode go online, automated and intelligent.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of a rules engine based business decision method of the present invention;
FIG. 2 is an architecture diagram of a rules engine based business decision system;
FIG. 3 is a schematic diagram of a rule compilation network and matching process;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, the present invention provides a business decision method based on a rule engine, which is applied to a business decision system of the rule engine, wherein the system includes a rule configuration server and a rule execution server, as shown in fig. 1, in the preferred embodiment of the business decision method based on the rule engine, the method includes the following steps:
step S10, the rule configuration server deploys the service configuration rule information in real time in a preset mode according to the rule strategy set pre-configured by the service party, stores the service configuration rule information in a database, independently simulates and tests different resources aiming at the different resources and outputs results, and sends the service configuration rule information to the rule execution server.
Wherein the step of independently testing different resources and outputting results for the different resources comprises:
and calculating and matching the input data by adopting a RETE algorithm of a rule engine and outputting a result.
When the RETE algorithm is used for pattern matching, the pattern matching is carried out according to the generated identification network, the types of non-root nodes in the network comprise 1-input nodes and 2-input nodes, the 1-input nodes form an Alpha network, and the 2-input nodes form a Beta network.
Specifically, the step of calculating a match for the input data and outputting the result by using the RETE algorithm of the rule engine includes:
match: finding out a work memory set conforming to the LHS part;
confilict resolution: selecting a rule for which a condition is satisfied;
act: content to perform RHS;
and returning to the Match step.
And step S20, the rule execution server executes a corresponding strategy according to the model data sent by the service calling party and the service configuration rule information, and outputs a decision result.
In this embodiment, the step of deploying, by the rule configuration server, the service configuration rule information in real time in a preset manner according to a rule policy set preconfigured by a service party includes:
and the rule configuration server deploys the service configuration rule information in real time in an HTTP mode according to a rule strategy set pre-configured by a service party.
The rule configuration server deploys service configuration rule information in real time in a preset mode according to a rule strategy set pre-configured by a service party, and the step of sending the service configuration rule information to a rule execution server comprises the following steps:
the rule configuration server deploys service configuration rule information in real time in a preset mode according to a rule strategy set pre-configured by a service party, generates DRL files conforming to the specifications of a Drools rule engine according to the service configuration rule information, and issues rule operation files to the rule execution server.
The step that the rule configuration server deploys the service configuration rule information in real time in a preset mode according to the rule strategy set pre-configured by the service party comprises the following steps:
and pre-configuring a rule strategy set, wherein the rule strategy set is a set of resources required by rule operation, defining the strategy set name, adding resource information after selecting a data model, and the resource information type comprises a strategy main flow, a rule set, a score card, a sub-decision flow, a programmable function, a hard coding function, a single-axis decision table and a double-axis decision table.
The system comprises a rule strategy set, a rule strategy main flow, a node of the strategy main flow can select start, end, the rule set, a score card, a programmable function, a hard coding function, a single-axis decision table, a double-axis decision table and the like, resources are connected into a flow chart through gateway connecting lines, and the flow node executes related instructions according to the sequence of the flow chart.
The present invention is further described in detail below with reference to fig. 1 to 3.
Compared with the prior art, the business decision method based on the rule engine has the following advantages:
1. and (4) based on the Drools technology development, a Rete algorithm is used, the condition that the same condition is evaluated for multiple times is avoided through caching, and the rule result is output efficiently.
2. The object structured processing is provided through the configuration model, the user-defined model is supported, various data structures are met, JSON format is adopted to flexibly joint the request data of each platform, the result is output by user definition, and the difference between the input parameter and the output parameter of each system is met.
3. The rules engine supports various rules and flow characteristics including policies, rule sets, score cards, decision flows, single-axis decision tables, dual-axis decision tables, functions, variables, and the like.
4. A flexible testing and service extension mechanism is provided, whether the rule set meets expectations or not can be tested in real time, and enterprise maintenance cost is reduced better.
5. And by the visual interface, business personnel can quickly adjust business rules according to market changes with lower learning cost, and the flexibility of own business is guaranteed.
The business decision method based on the rule engine adopts the following technical scheme for realizing the advantages:
defining a data model according to the needs of a service scene, customizing data parameters conforming to the service of the data model, wherein the data parameters support 7 data types such as Integer, Double, String, Boolean, Date, Entity, List and the like, the Entity data type supports infinite hierarchy, and the data types meet the configuration of most service scenes. And a complete data model definition is completed by defining parameters such as data types, names, descriptions, associated dictionaries and the like and returning data types and names of values. And the data model is displayed and edited by adopting a tree structure. Taking interview service as an example, service personnel collect relevant questions and alternative answers of common service scenes and complete the definition of a data model through data modeling.
The rule strategy set is a set of resources required by rule operation, the resource information is added after the strategy set is defined to be named and a data model is selected, and the resource information types comprise a strategy main flow, a rule set, a score card, a sub-decision flow, a programmable function, a hard coding function, a single-axis decision table, a double-axis decision table and the like. A rule strategy set has only one strategy main flow, nodes of the strategy flow can be selected to start and end, the rule set, a score card, a programmable function, a hard coding function, a single-axis decision table, a double-axis decision table and the like, resources are connected into a flow chart through gateway connecting lines, and the flow nodes execute related instructions according to the sequence of the flow chart.
Business staff can configure the information through the visual page and can configure complex business rules without compiling codes. And according to the information input by the service personnel, the rule configuration server generates a DRL file which accords with the specifications of a Drools rule engine, and releases the rule running file to the rule execution server.
The rule configuration server deploys the rules in real time in an HTTP mode, the rule configuration server can independently simulate and test different resources aiming at the different resources and output results, and a business party can determine whether the rules configured by the business target are correct or not according to the actual output results. And after the rule configuration is completed, the rule configuration server provides an HTTP interface for the service caller to call, the rule execution adopts a pure memory mode for calculation, the efficiency is extremely high, and finally, the output decision result is returned to the service caller.
The business decision method based on the rule engine is applied to a business decision system based on the rule engine, and comprises a rule configuration server, a rule execution server, a business caller and a database as shown in figure 2.
The business decision system based on the rule engine specifically comprises:
and the rule configuration server acquires and binds the fixed port of the local computer when the server is started, and provides the Restful interface service of the HTTP protocol to the outside through the IP address of the rule configuration server.
The rule configuration server is used for receiving the service configuration rule sent by the service party and storing the service configuration rule in the database.
The service configuration rule information sent by the service party includes the APPID of the defined rule set, the called version number, the data of the data model, and the like. And the service party sends the data in the JSON format to the rule configuration server, and the rule configuration server calculates and matches the input data by using the RETE algorithm of the rule engine and outputs a result.
The RETE algorithm is performed based on the generated authentication network when pattern matching is performed. The types of non-root nodes in the network are two types, 1-input nodes (also called alpha nodes) and 2-input nodes (also called beta nodes). The 1-input nodes form an Alpha network, and the 2-input nodes form a Beta network.
Each non-root node has a storage area. Wherein the 1-input node has an alpha storage region and an input port; the 2-input node is provided with a left storage area, a right storage area and a left input port and a right input port, wherein the left storage area is a beta storage area, and the right storage area is an alpha storage area. The minimum unit of storage area storage is a work storage area Element (WME), which is an Element established for a fact and used for matching with a pattern represented by a non-root node. Token is a list of WMEs that contains multiple WMEs for the left input of the 2-input node. Facts can be input to the right side of the 2-input node, and can also be input to the 1-input node.
Each non-root node represents a pattern that produces the left portion of the formula, and the path from the root node to the destination node represents the left portion of the formula.
The main flow of the RETE algorithm can be divided into the following steps:
match: finding out a work memory set conforming to the LHS part;
confilict resolution: selecting a rule for which a condition is satisfied;
act: content to perform RHS;
4. and returning to the step 1.
The RETE algorithm mainly improves the processing process of Match, matching is performed by constructing a network, and a rule compiling network and a matching process are shown in fig. 3.
The technical scheme is suitable for various decision scenes, such as automatically giving the credit loan line according to the credit information of the client, automatically approving or rejecting according to the interview information of the client, and automatically pushing the marketing information according to the client data. The rule set corresponds to different resources in different scenes, the rule set is formed by a plurality of rules into a whole, each rule generates a temporary result, the rule results also can generate a rule set temporary result, the rule set comprises a special built-in rule, and the built-in rule can acquire various temporary data and results generated by rule operation. The scoring cards give temporary results to different models through rules specified by the business parties, and the temporary results comprise each scoring item and the total score of one scoring card. The single-axis decision table realizes a value assignment action through different conditions, a temporary result cannot be generated, and the action process is only one. The double-axis decision table is an enhanced implementation of the single-axis decision table, can realize composite operation, and can more flexibly configure corresponding rules to realize the implementation. The function uses Java language characteristics, and can combine rules through a code mode, thereby providing higher flexibility. The decision flow provides the beginning, the end, the conditional gateway, the merging gateway and various resource selections, and all the resources are connected in series to form a whole by using a connection mode through the BPMN. The whole strategy also supports temporary variables, the scope only takes effect in the current strategy, and supports complex expression statistics, such as: quantity, summation, and sizing. The rule configuration server provides the publishing service to the server, and the publishing service can be deployed in real time. The test tool provides a simulation test and a unit test, the simulation test tests the whole strategy and obtains a corresponding decision result. Unit testing provides fine-grained testing for testing of a single resource.
And the rule execution server is used for receiving the model data sent by the service calling party, executing a corresponding strategy and outputting a decision result.
The service caller executes the specific strategy of the server by the HTTP calling rule, the rule executing server executes the corresponding rule by the strategy existing in the memory, and returns the decision result to the service caller.
The business decision method based on the rule engine has the advantages that: according to the technical scheme, the method and the system can get rid of the great dependence of the traditional operation decision on business personnel and IT personnel, reduce the enterprise cost, reduce the learning cost of a decision engine system, realize the real simplicity, rapidness and easiness in operation, shorten the strategy release period, deal with the environmental change in real time, make the risk data return on the ground, serve the risk policy and make more enterprises depending on the traditional decision mode go online, automated and intelligent.
In order to achieve the above object, the present invention further provides a service decision system based on a rule engine, where the system includes a rule configuration server, a rule execution server, a memory and a processor, where the memory stores a service decision program based on the rule engine, and the steps of the method according to the above embodiment are executed when the service decision program based on the rule engine is called by the processor, and are not described herein again.
In order to achieve the above object, the present invention further provides a computer-readable storage medium, where a service decision program based on a rule engine is stored in the computer-readable storage medium, and the service decision program based on the rule engine executes the steps of the method according to the above embodiments when being called by a processor, which is not described herein again.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. A business decision method based on a rule engine is applied to a business decision system of the rule engine, the system comprises a rule configuration server and a rule execution server, and the method comprises the following steps:
the rule configuration server deploys service configuration rule information in real time in a preset mode according to a rule strategy set pre-configured by a service party, stores the service configuration rule information into a database, independently simulates and tests different resources aiming at the different resources, outputs a result, and sends the service configuration rule information to a rule execution server; a business person of a business party configures a rule strategy set through a visual page, the business party determines whether a rule configured by a business target is correct or not according to an actual output result, the rule configuration is completed, and a rule configuration server provides an HTTP interface for a business caller to call;
the rule execution server executes a corresponding strategy according to the model data sent by the service calling party and the service configuration rule information, and outputs a decision result, and the rule execution adopts a pure memory mode for calculation;
the rule strategy set is a set of resources required by rule operation, the resource information is added after the strategy set is defined to be named and a data model is selected, and the resource information type comprises a strategy main flow, a rule set, a score card, a sub-decision flow, a programmable function, a hard coding function, a single-axis decision table and a double-axis decision table; one rule strategy set has only one strategy main flow, the nodes of the strategy main flow can select to start and end, the rule set, the score card, the programmable function, the hard coding function, the single-axis decision table and the double-axis decision table, resources are connected into a flow chart through gateway connecting lines, and the flow nodes execute related instructions according to the sequence of the flow chart;
the rule strategy set comprises a plurality of rules, each rule generates a temporary result, the rules generate a temporary result, the rule strategy set comprises special built-in rules, and the built-in rules can acquire various temporary data and results generated by rule operation; the scoring cards give temporary results to different models through rules specified by a service party, wherein the temporary results comprise the total score of each scoring item and one scoring card; the single-axis decision table realizes a value assignment action through different conditions, a temporary result cannot be generated, and only an action process is realized; the double-axis decision table is an enhanced implementation of a single-axis decision table, and can realize composite operation.
2. The rules engine based business decision method of claim 1, wherein the step of testing different resources independently for different resources and outputting results comprises:
and calculating and matching the input data by adopting a RETE algorithm of a rule engine and outputting a result.
3. The rules engine based business decision method of claim 2, wherein the RETE algorithm is performed according to the generated authentication network when performing pattern matching, the types of non-root nodes in the network are 1-input node and 2-input node, the 1-input node constitutes an Alpha network, and the 2-input node constitutes a Beta network.
4. The rules engine based business decision method of claim 3, wherein the step of computing matching on input data and outputting the result by using RETE algorithm of the rules engine comprises:
match: finding out a work memory set conforming to the LHS part;
confilict resolution: selecting a rule for which a condition is satisfied;
act: content to perform RHS;
and returning to the Match step.
5. The business decision method based on the rule engine as claimed in claim 1, wherein the step of deploying the business configuration rule information in real time by the rule configuration server side in a preset manner according to the rule policy set pre-configured by the business party comprises:
and the rule configuration server deploys the service configuration rule information in real time in an HTTP mode according to a rule strategy set pre-configured by a service party.
6. The business decision method based on the rule engine as claimed in claim 1, wherein the step of deploying the business configuration rule information by the rule configuration server in real time in a preset manner according to the rule policy set pre-configured by the business party and sending the business configuration rule information to the rule execution server comprises:
the rule configuration server deploys service configuration rule information in real time in a preset mode according to a rule strategy set pre-configured by a service party, generates DRL files conforming to the specifications of a Drools rule engine according to the service configuration rule information, and issues rule operation files to the rule execution server.
7. The business decision method based on the rule engine as claimed in claim 1, wherein the step of deploying the business configuration rule information in real time by the rule configuration server side in a preset manner according to the rule policy set pre-configured by the business party comprises:
and pre-configuring a rule strategy set.
8. A business decision system based on a rule engine, comprising a rule configuration server, a rule execution server, a memory and a processor, wherein the memory stores a business decision program based on the rule engine, and the business decision program based on the rule engine executes the steps of the method according to any one of claims 1 to 7 when being called by the processor.
9. A computer-readable storage medium having stored thereon a rules engine based business decision program which when invoked by a processor performs the steps of the method of any of claims 1 to 7.
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