Decision flow development method, device, equipment and storage medium

Abstract

The present application relates to the technical field of computer, especially to a decision flow development method, device and equipment and storage medium, the decision flow development method is applied to decision flow development system, the decision flow development system includes: configuration module, deployment module and decision module, the decision flow development method includes: providing decision model component for human-computer interaction with configuration personnel through configuration module, so that the configuration personnel configures component node to create decision process;When receiving deployment instruction, calling deployment module to deploy decision process to rule engine;When receiving decision request, calling target decision process corresponding to decision request from rule engine through decision module, generating decision result based on decision request and target decision process and returning.The present application realizes simplifying the operation of configuration personnel, and improves the convenience of configuration decision flow.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a decision flow development method, apparatus, device, and computer-readable storage medium. Background Technology

[0002] With government policy support for supply chain operations and the booming development of the supply chain finance market, more and more core enterprises, logistics companies, and e-commerce companies are making supply chain finance a key part of their strategic layout and increasing their investment in system digitalization. Data sharing and strategic collaboration among all participants in a supply chain finance platform, along with the establishment of a more scientific credit rating system, effectively reduce credit risk, improve overall supply chain efficiency, and lower transaction costs across the entire industry.

[0003] Currently, credit rating systems are typically built using a decision flow approach. The decision flow is configured primarily through hard coding, which makes it inflexible to expand and has poor computational efficiency, thus affecting the ease of configuring the decision flow. Summary of the Invention

[0004] The main objective of this invention is to provide a decision flow development method, apparatus, device, and computer-readable storage medium, which aims to improve the ease of configuring decision flows.

[0005] To achieve the above objectives, the present invention provides a decision flow development method, which is applied to a decision flow development system, the decision flow development system comprising: a configuration module, a deployment module, and a decision module;

[0006] The decision flow development method includes:

[0007] The configuration module provides a decision model component for human-computer interaction with configuration personnel, allowing them to configure component nodes to create decision processes.

[0008] Upon receiving a deployment instruction, the deployment module is invoked to deploy the decision-making process to the rule engine;

[0009] Upon receiving a decision request, the decision module invokes the target decision process corresponding to the decision request from the rule engine, generates a decision result based on the decision request and the target decision process, and returns it.

[0010] Optionally, the decision model represented by the decision model component includes a real-time model and a computational model;

[0011] The decision flow development method also includes:

[0012] The decision module inputs the business data carried by each decision request within a preset time period into the computational model at a preset time to generate model conclusions.

[0013] The model conclusions are applied to the real-time model so that the decision module can call the real-time model to make decisions based on the model conclusions.

[0014] Optionally, the step of generating and returning a decision result based on the decision request and the target decision process includes:

[0015] The decision module inputs the business data carried by the decision request into the decision model component of the target decision process to generate a decision result.

[0016] The decision-making module returns the decision result to the terminal device that sent the decision request.

[0017] Optionally, the decision flow development system further includes an interface module;

[0018] The component node also includes a docking node, wherein the docking node has pre-set editable third-party information;

[0019] The step of generating and returning a decision result based on the decision request and the target decision process includes:

[0020] The docking module reads the target third-party information from the docking node of the target decision-making process and calls third-party data based on the target third-party information.

[0021] The decision module inputs the business data carried by the decision request and the third-party data into the decision model component of the target decision process to generate a decision result.

[0022] The decision-making module returns the decision result to the terminal device that sent the decision request.

[0023] Optionally, the decision flow development method further includes:

[0024] Obtain the call information of the interface module when calling the third-party data;

[0025] The docking module generates a call report based on the call information.

[0026] Optionally, the step of calling the deployment module to deploy the decision-making process to the rule engine includes:

[0027] The deployment module is invoked to generate a database script according to the decision-making process;

[0028] The database script is stored in the rule engine's database.

[0029] Optionally, the component node includes: a fact node that provides selectable rule facts and a type node that provides selectable rule types;

[0030] The fact nodes are pre-set with editable rule variables and rule operations, and the rule types include ordinary rules, rule tables, rule trees, and scorecards.

[0031] Furthermore, to achieve the above objectives, the present invention also provides a decision flow development apparatus, which is applied to a decision flow development system, the decision flow development system comprising: a configuration module, a deployment module, and a decision module;

[0032] The decision flow development apparatus includes:

[0033] The first calling module is used to provide a decision model component for human-computer interaction with the configuration personnel through the configuration module, so that the configuration personnel can configure the component nodes to create a decision process;

[0034] The second invocation module is used to invoke the deployment module to deploy the decision process to the rule engine when a deployment instruction is received;

[0035] The third invocation module is used to, upon receiving a decision request, invoke the target decision process corresponding to the decision request from the rule engine through the decision module, generate a decision result based on the decision request and the target decision process, and return it.

[0036] In addition, to achieve the above objectives, the present invention also provides a decision flow development device, which includes a memory, a processor, and a decision flow development program stored in the memory and executable on the processor. When the decision flow development program is executed by the processor, it implements the steps of the decision flow development method described above.

[0037] In addition, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a decision flow development program, which, when executed by a processor, implements the steps of the decision flow development method described above.

[0038] In this invention, a decision model component for human-computer interaction with configuration personnel is provided through a configuration module, allowing configuration personnel to configure component nodes to create decision processes. When a deployment instruction is received, the deployment module is invoked to deploy the decision process to the rule engine. When a decision request is received, the decision module invokes the target decision process corresponding to the decision request from the rule engine, generates a decision result based on the decision request and the target decision process, and returns it.

[0039] Unlike configuring decision-making processes and models through coding, this invention allows decision flow configuration personnel to interact with decision model components via a configuration module. These components allow configuration personnel to configure node-to-node components to create decision flows, simplifying the process and improving the ease of configuring decision flows. Furthermore, this invention does not rely on the operator's skills or expertise for decision flow configuration, thus enhancing its applicability and operability.

[0040] Furthermore, this invention eliminates the need for configuration personnel to perform complex coding, reducing the time required for the configuration decision-making process and improving the work efficiency of configuration personnel. Attached Figure Description

[0041] Figure 1 This is a flowchart illustrating the first embodiment of the decision flow development method of the present invention;

[0042] Figure 2 This is a schematic diagram of the operation of a decision flow development system according to an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of the functional modules of the decision flow development device involved in the embodiment of the present invention;

[0044] Figure 4 This is a schematic diagram of the decision flow development device involved in the embodiment of the present invention;

[0045] Figure 5 This is a schematic diagram of the structure of a computer-readable storage medium involved in an embodiment of the present invention.

[0046] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0047] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0048] This invention provides a decision flow development method, which is applied to a decision flow development system, including a configuration module, a deployment module, and a decision module.

[0049] Specifically, in this embodiment, the configuration module provides a decision model component for human-computer interaction with configuration personnel, allowing them to configure decision processes. The decision process includes a start node, a decision model component, and an end node. The deployment module deploys the decision process created in the configuration module to the rule engine. The decision module retrieves the target decision process corresponding to the decision request from the rule engine, generates a decision result based on the decision request and the target decision process, and returns it.

[0050] It should be noted that, unlike configuring decision-making processes through coding, the decision flow development system in this embodiment allows decision flow configuration personnel to access interactive decision model components via a configuration module. These components allow configuration personnel to configure component nodes to create decision flows, simplifying the operation for configuration personnel and improving the convenience of configuring decision flows. In this embodiment, the decision flow development system does not rely on the operation and skills of configuration personnel for decision flow configuration, thus improving the applicability and operability of decision flow configuration.

[0051] Meanwhile, in this embodiment, the decision flow development system does not require configuration personnel to perform complex coding, which reduces the time spent configuring the decision flow and improves the work efficiency of configuration personnel.

[0052] Furthermore, in some feasible embodiments, the aforementioned component nodes include: fact nodes that provide selectable rule facts and type nodes that provide selectable rule types.

[0053] In this embodiment, the fact node can support a drop-down menu for configuration personnel to configure rule facts; similarly, the type node can support a drop-down menu for configuration personnel to configure rule types, including ordinary rules, rule tables, rule trees, and scorecards, thereby configuring the decision-making process.

[0054] In this embodiment, editable rule variables and rule operations are pre-set under the fact node, so that the configuration personnel can configure the judgment conditions of the rule fact by editing or using the pre-set data.

[0055] It should be noted that, compared to configuring decision models and processes through coding, this embodiment simplifies the configuration process for personnel, improving the convenience and operability of configuring the decision flow. Furthermore, compared to coding, this embodiment reduces the time required to configure the decision model, thereby increasing the efficiency of configuring the decision flow.

[0056] Based on the above decision flow development system, refer to Figure 1 The flowchart shown is a first embodiment of the decision flow development method of the present invention. The decision flow development method provided by the embodiment of the present invention includes:

[0057] Step S10: The configuration module provides a decision model component for human-computer interaction with the configuration personnel, so that the configuration personnel can configure the component nodes to create a decision process;

[0058] In this embodiment, a decision model component for human-computer interaction with configuration personnel is provided through a configuration module, allowing configuration personnel to configure decision-making processes. In a specific implementation, the decision model component can be displayed on a human-computer interaction interface provided by the configuration module, thus providing a human-computer interaction decision model component for configuration personnel; alternatively, the human-computer interaction decision model component can be used as the human-computer interaction interface, and no specific limitation is imposed here.

[0059] In a specific implementation, the configuration personnel can import external model data into the configuration module to configure the component nodes of the decision model component in order to configure the decision process. The model data can be coded data of the decision flow, a table file containing rule facts and rule variables, etc. The configuration personnel can also configure the component nodes in the decision model component provided by the configuration module according to actual needs to configure the decision process. In this embodiment, no specific restrictions are imposed.

[0060] Step S20: Upon receiving a deployment instruction, the deployment module is invoked to deploy the decision-making process to the rule engine;

[0061] After completing the configuration decision process in the configuration module, the configuration personnel can send deployment commands. Specifically, in one embodiment, a visual deployment button can be displayed on the decision model component provided by the configuration module, allowing the configuration personnel to send deployment commands by clicking the deployment button; in another embodiment, the configuration personnel can send deployment commands by entering command content in the decision model component, and the specific settings can be configured according to actual needs.

[0062] Upon receiving a deployment instruction, the deployment module is invoked to deploy the decision-making process to the rules engine.

[0063] In specific implementations, the decision-making process can be deployed directly to the rule engine, or the decision-making process can be converted into a script and then the script corresponding to the decision-making process can be deployed to the rule engine. No specific restrictions are imposed here.

[0064] Step S30: Upon receiving a decision request, the decision module calls the target decision process corresponding to the decision request from the rule engine, generates a decision result based on the decision request and the target decision process, and returns it.

[0065] Upon receiving a decision request, the decision module invokes the corresponding decision process (hereinafter referred to as the target decision process) from the rules engine.

[0066] Specifically, in one embodiment, the decision request may carry process information to specify the target decision process. In this embodiment, the decision module can determine the corresponding target decision process based on the process information carried in the decision request. In another embodiment, the decision module can also determine the target decision process to be invoked based on the business data carried in the decision request. No specific restrictions are imposed here.

[0067] In this embodiment, after the decision module calls the target decision process, a decision result is generated and returned based on the decision request and the target decision process.

[0068] Specifically, in one implementation, a conclusion can be drawn based on the decision request and the target decision process, for example, it is not recommended to issue a credit card to the user corresponding to the decision request; in another implementation, the analysis data in the decision process can be parsed into the file required by the decision request and then the file can be used as the decision result. There are no specific restrictions here, and it can be set according to actual needs.

[0069] In specific implementations, the process of generating decision results based on decision requests and target decision processes can vary depending on the target decision process. For example, in one implementation, when the decision model component of the target decision process does not have a third-party interface node, the decision result can be generated by directly inputting the business data carried by the decision request into the decision model component of the target decision process through the decision module. In another implementation, when the decision model component of the target decision process has a third-party interface node, the data from the third party needs to be retrieved first based on the interface node, and then the business data carried by the decision request and the third-party data are input into the decision model component of the target decision process to generate the decision result. The specific process is not limited here.

[0070] Furthermore, in some feasible embodiments, the component nodes in step S10 above include: a fact node that provides selectable rule facts and a type node that provides selectable rule types.

[0071] Among them, the fact nodes have pre-set editable rule variables and rule operations, and the rule types include ordinary rules, rule tables, rule trees and scorecards.

[0072] Specifically, in one implementation, the configuration user can select rule facts by clicking. Based on the rule facts determined by the configuration user, the corresponding rule variables and rule operations can be loaded dynamically. Specifically, the rule variables include comparison operators and editable comparison parameters. The comparison operators can be in symbolic form, such as greater than or less than symbols; or in string form, such as greater than or less than.

[0073] In another implementation, the configuration personnel can also edit the rule variables and rule operations according to actual needs. There are no specific restrictions here, and the settings can be made according to actual needs.

[0074] Specifically, in one implementation, the configuration personnel can select the rule type by clicking; in another implementation, the configuration personnel can also select the rule type by inputting a command. In this case, the configuration module can call the rule type corresponding to the input command to the type node.

[0075] Furthermore, in some feasible embodiments, step S20 above, which involves calling the deployment module to deploy the decision-making process to the rule engine, includes:

[0076] Step S201: Invoke the deployment module to generate a database script according to the decision-making process;

[0077] Step S202: Store the database script into the database of the rule engine.

[0078] In this embodiment, the decision-making process is deployed to the rule engine in the form of a script through the deployment module. Specifically, upon receiving a deployment instruction, the deployment module is invoked to generate a database script according to the decision-making process, and the database script is stored in the rule engine's database.

[0079] Unlike deploying decision-making processes through coding, this embodiment simplifies the operations of configuration personnel and improves the convenience of configuring decision flows. In this embodiment, the decision flow development system does not rely on the operations and skills of configuration personnel for decision flow configuration, thus improving the applicability and operability of decision flow configuration.

[0080] In this embodiment, the configuration module provides a decision model component for human-computer interaction with the configuration personnel, allowing the personnel to configure component nodes to create decision processes. Upon receiving a deployment instruction, the deployment module is invoked to deploy the decision process to the rule engine. Upon receiving a decision request, the decision module invokes the target decision process corresponding to the decision request from the rule engine, generates a decision result based on the decision request and the target decision process, and returns it.

[0081] Unlike configuring decision rules in a decision flow through coding, this embodiment allows decision flow configuration personnel to interact with decision model components provided by the configuration module. These components allow configuration personnel to configure component nodes to create decision processes, simplifying the operation for configuration personnel and improving the convenience of configuring decision flows.

[0082] In this embodiment, the decision flow configuration does not depend on the operation and skills of the configuration personnel, thus improving the applicability and operability of the decision flow configuration.

[0083] Meanwhile, this embodiment does not require configuration personnel to perform complex coding, reducing the time spent on configuration decision-making and improving the work efficiency of configuration personnel.

[0084] Furthermore, based on the first embodiment described above, a second embodiment of the decision flow development method of the present invention is proposed. In this embodiment, step S30 above: generating a decision result based on the decision request and the target decision flow includes:

[0085] Step S301: Input the business data carried by the decision request into the decision model component of the target decision process through the decision module to generate a decision result;

[0086] In this embodiment, the decision model component does not include a node for acquiring third-party data. Instead, the decision module can directly use the business data required for business decisions and make decisions based on the target decision process.

[0087] Specifically, decision requests can carry business data. Upon receiving a decision request, the decision module parses the request to obtain the business data. After parsing the business data, the decision module inputs it into the decision model component of the target decision process to generate the decision result.

[0088] Step S302: The decision result is returned to the terminal device that sent the decision request through the decision module.

[0089] In this embodiment, the decision module inputs the business data carried by the decision request into the decision model component of the target decision process to generate a decision result. After obtaining the decision result, the decision module returns the decision result to the terminal device that sent the decision request.

[0090] Furthermore, in some feasible embodiments, the above-mentioned decision flow development system also includes a docking module, which is used to dock with third-party service providers to obtain third-party data.

[0091] In this embodiment, the component node also includes a docking node, which has pre-set editable third-party information. In a specific implementation, the third-party information is information used to obtain third-party data. This third-party information may include: the address of the third-party service provider, the data interface of the third-party service provider, etc., and is not specifically limited here.

[0092] In this embodiment, step S30 above: generating a decision result based on the decision request and the target decision process includes:

[0093] Step S303: Read the target third-party information in the docking node of the target decision process through the docking module, and call the third-party data based on the target third-party information;

[0094] In this embodiment, a docking node is set up in the decision model component. At this time, when making decisions through the decision module, it is necessary to call third-party data provided by a third-party service provider. For example, credit record data can be retrieved from a bank's data center so that the decision module can use this third-party data for business decisions.

[0095] Specifically, in this embodiment, the third-party information set in the docking nodes of the target decision-making process decision model is referred to as target third-party information.

[0096] The module reads the target third-party information set in the docking nodes of the target decision-making process, and reads the address and interface of the third-party data required by the target decision-making process.

[0097] After reading the address and data interface of the third-party data required by the target decision-making process through the docking module, the corresponding third-party data is called through the docking module based on the above address and interface, so that the decision-making module can use the above third-party data to make decisions.

[0098] Specifically, in one embodiment, a communication connection is established between the docking module and the decision-making module. After the docking module retrieves third-party data, it can send the third-party data to the decision-making module for the decision-making module to use the data for decision-making. In another embodiment, after the docking module retrieves third-party data, it can upload the data to the decision flow development system. The workflow development system then sends the received third-party data to the decision-making module. The specific configuration can be adjusted according to actual needs and is not limited here.

[0099] Step S304: Through the decision module, the business data carried by the decision request and the third-party data are input into the decision model component of the target decision process to generate a decision result.

[0100] In this embodiment, the decision request may carry business data. Upon receiving the decision request, the decision module can parse the request to obtain the business data.

[0101] The decision module parses the decision request to obtain business data, and after receiving third-party data called by the docking module, it inputs the business data and third-party data into the decision model component of the target decision process to generate decision results.

[0102] Step S305: The decision result is returned to the terminal device that sent the decision request through the decision module.

[0103] In this embodiment, the decision module inputs the business data carried by the decision request into the decision model component of the target decision process to generate a decision result. After obtaining the decision result, the decision module returns the decision result to the terminal device that sent the decision request.

[0104] It should be noted that, compared to adding the call address of third-party data to the rule model through encoding, this embodiment allows configuration personnel to quickly and independently add and maintain the required third-party service provider information without relying on technical personnel. This improves the convenience of the configuration decision flow and enhances the applicability and operability of the decision flow configuration.

[0105] Furthermore, in some feasible embodiments, the above-described decision flow development method further includes:

[0106] Step S40: Obtain the call information of the docking module when calling the third-party data;

[0107] Step S50: Generate a call report based on the call information through the docking module.

[0108] In this embodiment, the docking module can also generate a call report based on the data call status. Specifically, it obtains the call information of the docking module when calling third-party data, and generates a call report based on the call information. This enables the classification and statistical management of data service providers, facilitating settlement processing for business personnel and improving the practicality of the decision flow development system.

[0109] In a specific implementation, the call report may include data consumption records and bills with different data service providers.

[0110] Furthermore, in some feasible embodiments, the decision model component represents a decision model including a real-time model and a computational model; the real-time model performs decision processing in real time, and the computational model generates conclusions based on multiple data conclusions.

[0111] In this embodiment, the decision flow development method further includes:

[0112] Step S60: The decision module inputs the business data carried by each decision request within a preset time period into the computational model at a preset time to generate model conclusions;

[0113] In this embodiment, the decision-making model is categorized into two types: real-time model and computational model. The computational model is used to generate model conclusions through batch task execution, while the implementation model provides model conclusions for the decision-making module to call upon the real-time model for decision-making.

[0114] Specifically, in this embodiment, the decision module inputs the business data carried by each decision request within a preset time period into the computational model at a preset time. The computational model then uses the business data input by the decision module within the preset time period to make decisions, thereby obtaining model conclusions and generating model conclusions.

[0115] In a specific implementation, the decision module can store the business data used in each business decision, and at a preset time, send the stored business data within a preset time period to the computational model component in the decision process. The computational model component can then be invoked to use the above business data to make a decision and arrive at the model conclusion.

[0116] In this embodiment, since different decision requests correspond to different decision processes, when storing business data, the decision processes can be classified and stored according to the different decision processes called by the decision module. When generating model conclusions, the decision module can send the business data of each category to the computational model component in the corresponding decision process.

[0117] Furthermore, in this embodiment, the decision flow development system may include a storage module for storing business data used in business decision-making.

[0118] It is understood that, in one implementation, when the decision model component includes a docking node, the third-party data called through the docking module and the business data received through the decision module can generate model conclusions in the same way as described above, which will not be elaborated here.

[0119] Step S70: Apply the model conclusions to the real-time model, so that the decision module can call the real-time model to make a decision based on the model conclusions.

[0120] After obtaining the model conclusions through the computational model, the model conclusions are applied to the real-time model. When making business decisions, the decision module calls the implementation model in the decision model component of the target decision process to make decisions based on the model conclusions in the real-time model.

[0121] Compared to existing rule-based operations that use real-time algorithms, this embodiment improves the computational efficiency of the decision-making model, thereby increasing the amount of data processed and the processing efficiency of business decisions per unit time.

[0122] In this embodiment, upon receiving a decision request, the decision module inputs the business data carried in the decision request into the decision model component of the target decision process to generate a decision result. Unlike decisions made using logical judgments, this embodiment simplifies the decision-making process and improves the efficiency of business decisions.

[0123] Furthermore, in some feasible embodiments, reference is made to Figure 2 , Figure 2 This is a schematic diagram illustrating the application of a decision flow development system according to an embodiment of the present invention. In this embodiment, the decision flow development system includes a configuration module, a deployment module, a decision module, and a docking module (i.e., Figure 2 (The docking center is shown in the image).

[0124] In this embodiment, a configuration module provides a human-computer interaction interface for configuration personnel to configure the decision-making process and customize the decision node page. This embodiment allows configuration personnel to configure different decision-making processes based on different business scenarios.

[0125] This embodiment involves business scenarios including: industrial finance platforms, supply chain business platforms, supply chain finance, internet platforms, and cloud platforms. Specifically, refer to... Figure 2 The business scenarios involved in this embodiment may include: investment / financing, fund management, micro-loan, guarantee and mortgage services, real estate risk control, etc. It is understood that, based on actual needs, configuration modules can also be used to allow configuration personnel to create additional services. Figure 2 The decision-making processes for other business operations besides those shown in the diagram.

[0126] In this embodiment, a decision model component for human-computer interaction with the configuration personnel is provided by the configuration module, allowing the personnel to configure the component nodes. In this embodiment, the component nodes include fact nodes, type nodes, and interface nodes. Specifically, configuring fact nodes includes configuring rule facts, rule variables, and rule operation methods; configuring type nodes involves configuring rule types; and configuring interface nodes involves configuring relevant information for obtaining third-party data.

[0127] Specifically, in this embodiment, the configuration module supports configuring fact nodes in different ways. For example, in one implementation, the configuration items of fact nodes in the decision model component can be implemented via page clicks using native JavaScript technology, allowing configuration personnel to select rule facts by clicking on the fact nodes. Based on the rule facts selected by the configuration personnel, the configuration module dynamically associates rule variables to generate AND, OR, and NOT logical expressions. Through reflection, the configuration module filters and displays a set of appropriate rule operation methods based on the field type of the rule facts.

[0128] In another embodiment, the configuration module also provides an import interface for human-computer interaction with the configuration personnel. In this embodiment, the configuration personnel can use the import interface provided by the configuration module to use commonly used Excel files as templates to quickly and effectively generate the required fact node data (i.e., rule facts and rule variables) through offline editing and online import.

[0129] In this embodiment, the type node provides selectable rule types, specifically, such as... Figure 2 As shown, rule types include several representations: ordinary rules, rule tables, rule trees, and scorecards. A configuration module allows users to configure type nodes. This can be achieved through native JavaScript technology, enabling users to select rule types by clicking on fact nodes.

[0130] In this embodiment, a configuration module allows configuration personnel to configure the interface nodes. This can be achieved using parametric configuration technology, where editable information is pre-set in the interface nodes within the decision model component provided by the configuration module, allowing configuration personnel to edit third-party information according to actual needs. Based on this interface node configuration method, this embodiment implements secure encryption and decryption methods when calling third-party data to ensure the security of obtaining third-party data. Therefore, this embodiment enables configuration personnel to quickly and independently add and maintain the necessary third-party service provider information without relying on technical personnel, improving the operability and ease of use of the decision-making process configuration.

[0131] In this embodiment, the decision model component, representing the decision model, is further categorized into two types in its design and implementation: real-time model and computational model. Specifically, in this embodiment, the real-time model makes real-time decisions based on the conclusions obtained from the computational model. This real-time model uses caching technology and high-concurrency programming technology to support high-concurrency online transaction scenarios. In this embodiment, the computational model adopts a day-end batch task execution mode. That is, at the end of the day, it uses data slicing, multi-threaded processing, and segmented submission techniques to make decisions using the day's business data to derive model conclusions. Based on this, this embodiment can improve the amount of data processed and the processing efficiency of the decision flow development system per unit time.

[0132] In this embodiment, a third-party service provider is connected via an interface module to access third-party data. Specifically, refer to... Figure 2 In this embodiment, third-party data includes at least: government data, internet data, and third-party credit data. It is understood that, based on the actual needs of business decision-making, additional data can be obtained through the interface module. Figure 2 Other third-party data besides the third-party data types shown.

[0133] Furthermore, this embodiment can also achieve categorized statistical management of data service providers through the docking module, and regularly generate data consumption records and bills between different data service providers to facilitate settlement processing for business personnel.

[0134] Based on the above, refer to Figure 2 In this embodiment, the specific process of making business decisions can be as follows: when a decision request is received, the decision module calls the corresponding target decision process from the rule engine according to the business scenario indicated by the decision request, such as the risk monitoring decision process corresponding to the real estate risk control business scenario.

[0135] When entering the docking node of the decision model component in the target decision-making process, the docking module calls the corresponding third-party data based on the third-party information configured in the docking node.

[0136] When entering the decision node of the decision model component in the target decision process, the decision module inputs the business data and third-party data carried in the decision request into the target decision process to generate a decision result. The format of the decision result is consistent with the rule type configured in the decision model component of the target process, and the decision result matches the business scenario. For example, the decision result corresponding to the real estate risk control business scenario is a risk identification result.

[0137] After generating the decision result, the decision module outputs the decision result and sends it to the terminal device that issued the decision request.

[0138] Furthermore, the present invention also provides a decision flow development apparatus, which is applied to a decision flow development system, the decision flow development system including: a configuration module, a deployment module, and a decision module;

[0139] Reference Figure 3 , Figure 3 This is a schematic diagram of the functional modules of the decision flow development device according to an embodiment of the present invention. The decision flow development device of the present invention includes:

[0140] The first calling module 10 is used to provide a decision model component for human-computer interaction with the configuration personnel through the configuration module, so that the configuration personnel can configure the component nodes to create a decision process;

[0141] The second invocation module 20 is used to invoke the deployment module to deploy the decision process to the rule engine when a deployment instruction is received;

[0142] The third invocation module 30 is used to, upon receiving a decision request, invoke the target decision process corresponding to the decision request from the rule engine through the decision module, generate a decision result based on the decision request and the target decision process, and return it.

[0143] Furthermore, the decision model components represent decision models including real-time models and computational models;

[0144] The aforementioned decision flow development apparatus also includes a fourth invocation module, which is used for:

[0145] The decision module inputs the business data carried by each decision request within a preset time period into the computational model at a preset time to generate model conclusions.

[0146] The model conclusions are applied to the real-time model so that the decision module can call the real-time model to make decisions based on the model conclusions.

[0147] Furthermore, the aforementioned third calling module 30 is also used for:

[0148] The decision module inputs the business data carried by the decision request into the decision model component of the target decision process to generate a decision result.

[0149] The decision-making module returns the decision result to the terminal device that sent the decision request.

[0150] Furthermore, the decision flow development system also includes an interface module;

[0151] The component node also includes a docking node, wherein the docking node has pre-set editable third-party information;

[0152] The aforementioned third calling module 30 is also used for:

[0153] The docking module reads the target third-party information from the docking node of the target decision-making process and calls third-party data based on the target third-party information.

[0154] The decision module inputs the business data carried by the decision request and the third-party data into the decision model component of the target decision process to generate a decision result.

[0155] The decision-making module returns the decision result to the terminal device that sent the decision request.

[0156] Furthermore, the aforementioned decision flow development apparatus also includes a fifth invocation module, which is used for:

[0157] Obtain the call information of the interface module when calling the third-party data;

[0158] The docking module generates a call report based on the call information.

[0159] Furthermore, the second calling module 20 described above is also used for:

[0160] The deployment module is invoked to generate a database script according to the decision-making process;

[0161] The database script is stored in the rule engine's database.

[0162] Furthermore, the component node includes: a fact node that provides selectable rule facts and a type node that provides selectable rule types;

[0163] The fact nodes are pre-set with editable rule variables and rule operations, and the rule types include ordinary rules, rule tables, rule trees, and scorecards.

[0164] Each functional module of the decision flow development device implements the steps of the decision flow development method described above during its operation.

[0165] Furthermore, the present invention also provides a decision flow development device. (See reference...) Figure 4 , Figure 4 This is a schematic diagram of the decision flow development device involved in an embodiment of the present invention. Specifically, the decision flow development device in this embodiment can be a device for locally running a decision flow development system.

[0166] like Figure 4As shown, the decision flow development device of this embodiment may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0167] The memory 1005 is disposed on the main body of the decision flow development device. The memory 1005 stores a program that, when executed by the processor 1001, performs corresponding operations. The memory 1005 also stores parameters used by the decision flow development device. The memory 1005 can be a high-speed RAM or a stable, non-volatile memory, such as a disk drive. Optionally, the memory 1005 can also be a storage device independent of the aforementioned processor 1001.

[0168] Those skilled in the art will understand that Figure 4 The structure of the decision flow development device shown does not constitute a limitation on the decision flow development device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0169] like Figure 4 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and a decision flow development program.

[0170] exist Figure 4 In the decision flow development device shown, the processor 1001 can be used to call the decision flow development program stored in the memory 1005 and perform the following operations:

[0171] The configuration module provides a decision model component for human-computer interaction with configuration personnel, allowing them to configure component nodes to create decision processes.

[0172] Upon receiving a deployment instruction, the deployment module is invoked to deploy the decision-making process to the rule engine;

[0173] Upon receiving a decision request, the decision module invokes the target decision process corresponding to the decision request from the rule engine, generates a decision result based on the decision request and the target decision process, and returns it.

[0174] Furthermore, the processor 1001 can also be used to call the decision flow development program stored in the memory 1005 and perform the following operations:

[0175] The decision module inputs the business data carried by each decision request within a preset time period into the computational model at a preset time to generate model conclusions.

[0176] The model conclusions are applied to the real-time model so that the decision module can call the real-time model to make decisions based on the model conclusions.

[0177] Furthermore, the processor 1001 can also be used to call the decision flow development program stored in the memory 1005 and perform the following operations:

[0178] The decision module inputs the business data carried by the decision request into the decision model component of the target decision process to generate a decision result.

[0179] The decision-making module returns the decision result to the terminal device that sent the decision request.

[0180] Furthermore, the processor 1001 can also be used to call the decision flow development program stored in the memory 1005 and perform the following operations:

[0181] The docking module reads the target third-party information from the docking node of the target decision-making process and calls third-party data based on the target third-party information.

[0182] The decision module inputs the business data carried by the decision request and the third-party data into the decision model component of the target decision process to generate a decision result.

[0183] The decision-making module returns the decision result to the terminal device that sent the decision request.

[0184] Furthermore, the processor 1001 can also be used to call the decision flow development program stored in the memory 1005 and perform the following operations:

[0185] Obtain the call information of the interface module when calling the third-party data;

[0186] The docking module generates a call report based on the call information.

[0187] Furthermore, the processor 1001 can also be used to call the decision flow development program stored in the memory 1005 and perform the following operations:

[0188] The deployment module is invoked to generate a database script according to the decision-making process;

[0189] The database script is stored in the rule engine's database.

[0190] Furthermore, the component node includes: a fact node that provides selectable rule facts and a type node that provides selectable rule types;

[0191] The fact nodes are pre-set with editable rule variables and rule operations, and the rule types include ordinary rules, rule tables, rule trees, and scorecards.

[0192] Furthermore, the present invention also provides a computer-readable storage medium. (See reference...) Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer-readable storage medium according to an embodiment of the present invention. The computer-readable storage medium stores a decision flow development program, which, when executed by a processor, implements the steps of the decision flow development method described above.

[0193] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0194] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0195] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a decision flow development device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0196] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A decision flow development method, characterized in that, The decision flow development method is applied to a decision flow development system, which includes a configuration module, a deployment module, and a decision module. The decision flow development method includes the following steps: The configuration module provides a decision model component for human-computer interaction with configuration personnel, allowing them to configure component nodes to create decision processes. The component nodes include fact nodes; the dynamic association and filtering mechanism of the configuration module includes: Based on the rule facts selected by the configuration personnel, the configuration module dynamically associates rule variables to generate AND, OR, and NOT logical expression. By using reflection, the configuration module can filter and display a set of appropriate rule operation methods based on the field type to which the rule fact belongs. Upon receiving a deployment instruction, the deployment module is invoked to deploy the decision-making process to the rule engine; Upon receiving a decision request, the decision module invokes the target decision process corresponding to the decision request from the rule engine, generates a decision result based on the decision request and the target decision process, and returns it. The step of generating and returning a decision result based on the decision request and the target decision process includes: The decision module inputs the business data carried by the decision request into the decision model component of the target decision process to generate a decision result. The decision-making module returns the decision result to the terminal device that sent the decision request; The decision flow development system further includes a docking module; the component node further includes a docking node, which has pre-set editable third-party information; the step of generating and returning a decision result based on the decision request and the target decision process includes: The docking module reads the target third-party information from the docking node of the target decision-making process and calls third-party data based on the target third-party information. The decision module inputs the business data carried by the decision request and the third-party data into the decision model component of the target decision process to generate a decision result. The decision-making module returns the decision result to the terminal device that sent the decision request.

2. The decision flow development method as described in claim 1, characterized in that, The decision model components represent decision models including real-time models and computational models; The decision flow development method also includes: The decision module inputs the business data carried by each decision request within a preset time period into the computational model at a preset time to generate model conclusions. The model conclusions are applied to the real-time model so that the decision module can call the real-time model to make decisions based on the model conclusions.

3. The decision flow development method as described in claim 1, characterized in that, The decision flow development method also includes: Obtain the call information of the interface module when calling the third-party data; The docking module generates a call report based on the call information.

4. The decision flow development method as described in claim 3, characterized in that, The step of calling the deployment module to deploy the decision-making process to the rule engine includes: The deployment module is invoked to generate a database script according to the decision-making process; The database script is stored in the rule engine's database.

5. The decision flow development method as described in any one of claims 1 to 4, characterized in that, The component nodes include: fact nodes that provide selectable rule facts and type nodes that provide selectable rule types; The fact nodes are pre-set with editable rule variables and rule operations, and the rule types include ordinary rules, rule tables, rule trees, and scorecards.

6. A decision flow development apparatus, characterized in that, The decision flow development method is applied to a decision flow development system, which includes a configuration module, a deployment module, and a decision module. The decision flow development apparatus includes: The first calling module is used to provide a decision model component for human-computer interaction with the configuration personnel through the configuration module, so that the configuration personnel can configure the component nodes to create a decision process; The second invocation module is used to invoke the deployment module to deploy the decision process to the rule engine when a deployment instruction is received; The third invocation module is used to, upon receiving a decision request, invoke the target decision process corresponding to the decision request from the rule engine through the decision module, generate a decision result based on the decision request and the target decision process, and return it. The third calling module is configured to: input the business data carried by the decision request into the decision model component of the target decision process through the decision module to generate a decision result; and return the decision result to the terminal device that sent the decision request through the decision module. The decision flow development system further includes a docking module; the component node also includes a docking node, which has pre-set editable third-party information; the third invocation module is used to: read the target third-party information in the docking node of the target decision flow through the docking module, and invoke third-party data based on the target third-party information; input the business data carried by the decision request and the third-party data into the decision model component of the target decision flow through the decision module to generate a decision result; and return the decision result to the terminal device that sent the decision request through the decision module; wherein, the component node includes a fact node; the first invocation module is also used to: dynamically associate rule variables through the configuration module based on the rule facts selected by the configuration personnel to generate AND, OR, and NOT logical relation expressions; and through reflection mechanism, filter and display a set of adapted rule operation methods based on the field type of the rule facts through the configuration module.

7. A decision flow development device, characterized in that, The decision flow development device includes: a memory, a processor, and a decision flow development program stored on the memory and executable on the processor, the decision flow development program being configured to implement the steps of the decision flow development method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a decision flow development program, which, when executed by a processor, implements the steps of the decision flow development method as described in any one of claims 1 to 5.

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