Flow scheduling control method and system based on rule decision diagram, medium and equipment

Abstract

The invention provides a flow scheduling control method and system based on a rule decision diagram, a medium and equipment, and the method comprises the steps: obtaining a service request of a user side, and carrying out the recognition based on the service request to obtain a service scene code; processing the service request by using the constructed service decision diagram to obtain a processing result, and performing result judgment on a function set in the service decision diagram based on the service scene code; the processing result is fed back to the user side, the processing result at least comprises an end result, and the end result is correspondingly from a check point or an end node in the service decision diagram. Through platform integration and link calling, flexible process arrangement and function scheduling are innovatively realized, corresponding operations can be automatically triggered according to different conditions and requirements by configuring the rule set, the rule can be flexibly configured in real time to perform function combination under complex services, the efficiency of the system is improved, and the system performance is improved. And the difficulty of complex service logic processing is reduced.

Description

Technical Field

[0001] The present invention relates to the field of decision graphs and data processing technology, and in particular to a flow scheduling control method, system, medium and equipment based on rule decision graphs. Background Art

[0002] A decision graph is a graphical model used to represent and explain decision-making processes. It's an extension of the decision tree, offering greater flexibility and visualization. A decision graph typically consists of a decision node, representing a decision point where a decision must be made based on certain conditions or rules; a result node, representing a result or output, where a specific outcome or decision is given; a decision edge, representing a decision path (the path from one decision node to another); and a result edge, representing a result path (the path from one result node to another).

[0003] Currently, when applying it, functions are developed in a customized manner, and the results are summarized through parallel calls. Among them, the existing technical solutions need to face the following problems: First, after the function is developed, it needs to be coupled with other functions of the current system to realize the product requirement function; second, the customized code development has the problem of outdated business points being difficult to clean up; third, the function points are isolated and cannot be based on the function combination relationship under the rule configuration, and complex business logic cannot be easily implemented. In addition, because there is no logical relationship between the function points, all the functions of the corresponding business configuration will be called every time, resulting in a waste of resources. Summary of the Invention

[0004] The purpose of the present invention is to provide a flow scheduling control method, system, medium and device based on a rule decision diagram, which are used to solve the problem of flow scheduling control based on a rule decision diagram.

[0005] In a first aspect, the present application provides a flow scheduling control method based on a rule decision graph, the method comprising:

[0006] Obtaining a service request from a user terminal, wherein a service scenario code is obtained based on the service request identification;

[0007] Processing the business request using the constructed business decision graph to obtain a processing result, wherein a result judgment is performed on the function set in the business decision graph based on the business scenario code;

[0008] feedback the processing result to the user terminal, wherein the processing result comprises at least one end result corresponding to a checkpoint or an end node in the business decision graph.

[0009] In a possible implementation of the present application, the method further comprises constructing the business decision graph, specifically comprising:

[0010] acquiring input basic data, wherein the basic data comprises at least metadata, logical routes and business scenario codes;

[0011] creating an initial decision graph, wherein the initial decision graph comprises at least two decision trees;

[0012] performing connection processing on the initial decision graph based on the basic data to obtain the business decision graph.

[0013] In a possible implementation of the present application, the performing connection processing on the initial decision graph based on the basic data to obtain the business decision graph specifically comprises:

[0014] identifying initial nodes, end nodes, checkpoints, decision nodes and meta functions based on the metadata;

[0015] completing link connection of each decision node based on the logical routes to obtain a function set, wherein the checkpoints are arranged between each two function sets, and the function set comprises a plurality of meta functions;

[0016] obtaining the constructed business decision graph based on the initial nodes, the end nodes, the function set and the checkpoints, wherein the decision nodes comprise at least serial decision nodes, parallel decision nodes, weight routing decision nodes and failure routing decision nodes.

[0017] In a possible implementation of the present application, the method further comprises:

[0018] updating the metadata in the business decision graph based on the basic data, wherein,

[0019] judging whether the current metadata exists in the business decision graph, wherein,

[0020] if not, adding the newly added metadata as a new meta function to the corresponding function set in combination with the corresponding logical route;

[0021] if yes, performing data update on the old version of the meta function based on the newly added metadata to replace the old version of the meta function.

[0022] In a possible implementation of the present application, obtaining the business scenario code based on the business request identification specifically includes: performing data processing based on the business request input by the user end to obtain the business scenario code, which at least includes performing text recognition on the business request to obtain a request recognition result, and matching a preset scenario code library based on the request recognition result to obtain the business scenario code.

[0023] In a possible implementation of the present application, the process of processing the service request using the constructed service decision graph to obtain a processing result specifically includes:

[0024] Matching the business decision diagram based on the business scenario code corresponding to the business request to obtain a corresponding preset function set;

[0025] The processing result is obtained by performing a logical judgment on the business request based on the meta-function in the preset function set, including outputting the processing result based on the detection result of the checkpoint, or outputting the processing result based on the detection result of the end node.

[0026] In a possible implementation of the present application, the business scenario code corresponding to the business request is matched with the business decision diagram to obtain the corresponding preset function set, specifically including: loading a function engine to capture the output of the meta-function under the current business scenario and the judgment of the gate logic to obtain the corresponding meta-function to be executed as the preset function set.

[0027] In a second aspect, the present application provides a flow scheduling control system based on a rule decision graph, the system comprising:

[0028] An acquisition module, configured to acquire a service request from a user terminal, wherein a service scenario code is obtained based on the service request identification;

[0029] a processing module, configured to process the business request using the constructed business decision graph to obtain a processing result, wherein a result judgment is performed on the function set in the business decision graph based on the business scenario code;

[0030] A feedback module is used to feed back the processing result to the user end, wherein the processing result includes at least one end result, and the end result corresponds to a checkpoint or end node in the business decision graph.

[0031] In a third aspect, the present application provides a computer-readable storage medium as described above, on which a computer program is stored, and when the program is executed by a processor, the flow scheduling control method based on the rule decision diagram is implemented.

[0032] In a fourth aspect, the present application provides an electronic device as described above, comprising a processor and a memory; wherein the memory is configured to store a computer program, and the processor is configured to load and execute the computer program, so that the electronic device performs the rule-based decision graph flow scheduling control method.

[0033] As described above, the rule-based decision graph flow scheduling control method, system, medium and device of the present application have the following beneficial effects: firstly, starting from a complex business scenario, supporting high-level abstraction for function points as one of the decision node processing logic, upgrading the concept of decision tree to decision graph, explaining the execution flow with a graphical model, achieving flexible combination instead of isolated execution, and being able to cope with more complex business scenarios; secondly, it can realize whether to call the related function point according to the result decision of the pre-node, that is, whether to flow to the corresponding decision point, reducing unnecessary function calls; thirdly, it can realize online configuration, version control, approval and release, etc. logic, which can guarantee the safety and integrity of the decision logic. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1 A scenario application diagram is shown for the rule-based decision graph flow scheduling control method of the present application in an embodiment;

[0035] Figure 2 A method step schematic diagram is shown for the rule-based decision graph flow scheduling control method of the present application in an embodiment;

[0036] Figure 3 An application flowchart is shown for the rule-based decision graph flow scheduling control method of the present application in an embodiment;

[0037] Figure 4 A method step schematic diagram is shown for the rule-based decision graph flow scheduling control method of the present application in an embodiment;

[0038] Figure 5 A method step schematic diagram is shown for the rule-based decision graph flow scheduling control method of the present application in an embodiment;

[0039] Figure 6 A business scenario access business decision graph application flowchart is shown for the rule-based decision graph flow scheduling control method of the present application in an embodiment;

[0040] Figure 7 A method step schematic diagram is shown for the rule-based decision graph flow scheduling control method of the present application in an embodiment;

[0041] Figure 8Shown is an application flow chart of meta-function maintenance in an embodiment of the flow scheduling control method based on rule decision diagram of the present invention;

[0042] Figure 9 Shown is a schematic structural diagram of a flow scheduling control system based on a rule decision diagram in one embodiment of the present invention;

[0043] Figure 10 Shown is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

[0044] Component number description

[0045] Steps S202 to S206

[0046] Steps S402 to S406

[0047] Steps S502 to S506

[0048] Steps S702 to S708

[0049] 90 Flow Scheduling Control System Based on Rule Decision Diagram

[0050] 91 Get Module

[0051] 92 processing modules

[0052] 93 Feedback Module DETAILED DESCRIPTION

[0053] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0054] It should be noted that the illustrations provided in the following embodiments are merely schematic illustrations of the basic concept of the present invention. Therefore, the illustrations only show components related to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0055] The application can realize flexible process arrangement and function scheduling by using a decision graph and a decision engine, wherein online construction of the decision graph is realized, and flexible function combination and business decision output based on business are realized. The specific innovation lies in maintaining data by using meta functions, and quickly and flexibly outputting decision results for different business scenario processes based on the decision engine. Referring to Figure 1 The decision graph is constructed by using meta functions as basic component units, so that corresponding decision results can be obtained by processing according to the business request of a requesting user. The constructed decision graph specifically consists of a decision tree, the decision tree includes a plurality of meta functions, and the meta functions can be changed and replaced. New functions or modified functions are added through metadata.

[0056] Specifically, refer to Figure 2 In an embodiment of the application, the rule-based decision graph flow scheduling control method comprises the following steps:

[0057] In step S202, a business request of a user terminal is obtained, wherein a business scenario code is identified based on the business request;

[0058] In step S204, a business decision graph is constructed, and the business request is processed to obtain a processing result by using the constructed business decision graph, wherein a result judgment is made on a function set in the business decision graph based on the business scenario code;

[0059] In step S206, the processing result is fed back to the user terminal, wherein the processing result at least includes an end result, and the end result corresponds to a checkpoint or an end node in the business decision graph.

[0060] It should be noted that, in this embodiment, as shown in Figure 3 The application flowchart of the rule-based decision graph flow scheduling control method is shown. For the constructed business decision graph, it is first captured and loaded into a cache for subsequent use. Then, after a business request enters, that is, a business request of a user terminal is obtained, a corresponding business scenario code is identified based on the business request. Data processing is performed in the business decision graph to be used for subsequent use to load rules based on the business scenario code. A result judgment is made on a function set in the business decision graph based on the business scenario code. The execution record is landed synchronously. First, starting from a starting node, the meta function configuration in the decision graph is obtained, the rules are executed, and the logic is followed to execute between different function sets. When crossing the function set, the checkpoint is intervened to determine whether the response is ended at the checkpoint. If the response is ended at the checkpoint, it is determined that it is an end node. Then, the corresponding end result is output. If the response is not ended at the checkpoint, when the logic goes to a specific end node, the current flow is ended, and the corresponding end result is output.

[0061] In particular, in this embodiment, the business scenario code is identified based on the service request, specifically including: performing data processing based on the service request input by the user terminal to obtain the business scenario code, wherein at least including performing character recognition on the service request to obtain a request recognition result, and matching the request recognition result with a preset scenario code library to obtain the business scenario code, wherein matching the business scenario code corresponding to the service request with the business decision graph obtains a corresponding preset function set, which means that after the user issues a service request, the corresponding business scenario code can be analyzed according to the specific request content, so as to match the meta-function related to the corresponding business scenario code in the business decision graph to obtain a preset function set based on the corresponding business scenario code, so as to perform rule judgment to output the final decision result.

[0062] Further, in this embodiment, the processing result is obtained by logically judging the service request based on the meta-function in the preset function set, which includes outputting the processing result based on the detection result of the checkpoint or outputting the processing result based on the detection result of the end node, which means that the checkpoint set between different function sets can terminate the process, which is used for waiting for the process of asynchronous result, so as to reduce unnecessary function calls, wherein, for example, the business decision graph supports serial, parallel, weight routing and failure routing for combination, and the failure routing can correspond to the detection result of the checkpoint in this embodiment. When the checkpoint is detected, if there is an error in the checkpoint detection, an error can be directly reported, the current process is terminated, and subsequent function calls are not needed, so as to save resources.

[0063] Further, the corresponding preset function set is obtained by matching the business scenario code corresponding to the service request with the business decision graph, which specifically includes: loading a function engine to capture the output of the meta-function and the judgment of the gate logic under the current business scenario, so as to obtain the meta-function that needs to be executed as the preset function set. Specifically, for example, the user service request is a "cargo number", which needs to be detected and output. The decision engine responds based on the "cargo number" and inputs the service request to the meta-function related to the cargo number for detection, wherein the service request is first input to the "cargo number rule detection" meta-function module for detection, and there is a result code. Then, based on the gate logic judgment, the current result code can be searched for the hit result code rule, and the context is input to the next related meta-function module, so as to perform a loop logic until the checkpoint ends or the end node ends, and output the final decision end result, such as "the cargo number contains a prohibited field" or "the cargo number rule does not comply with the ** rule".

[0064] Further, in an embodiment of the present application, the method further comprises constructing the business decision graph, i.e. constructing the decision graph online according to the inputted basic data, specifically, as shown in Figure 4 the method comprises the following steps:

[0065] In step S402, the inputted basic data is acquired, wherein the basic data at least includes metadata, logical flow and business scenario code;

[0066] In step S404, an initial decision graph is created, wherein the initial decision graph at least includes two decision trees;

[0067] In step S406, the initial decision graph is connected based on the basic data to obtain the business decision graph.

[0068] It should be noted that in the present embodiment, the meta function is the minimum execution unit of the decision tree, and the decision graph is composed of the decision tree, thus, the inputted basic data is acquired first, and the business decision graph is obtained through connection analysis based on the basic data, specifically, the basic data at least includes metadata, logical flow and business scenario code, wherein the business scenario code is associated with specific information in the decision graph, an initial decision graph is created, the initial decision graph is filled and connected (specifically, the decision edge and the result edge are connected) based on the basic data, the user serial flow is connected, and the execution flow is ended based on the set end node, thus, the business decision graph construction is completed.

[0069] Specifically, each meta function is cohesive to the minimum function point, and provides a public API (Application Programming Interface) for parameter input and result output, for example, a "article number rule detection" meta function uses regular rule detection capability to aggregate the capability, so as to independently provide the capability, and obtain the rule detection result ("0" represents passing, and "-1" represents rejection), the meta functions similar to the example are combined into a complete detection link graph, and the logical flow, i.e. the "gate" logic, is marked in the graph, so as to be assembled into a complete decision tree, and multiple decision trees are assembled into a decision graph.

[0070] Further, in an embodiment of the present application, as shown in Figure 5 the method comprises the following steps:

[0071] In step S502, the initial node, the end node, the check point, the decision node and the meta function are identified based on the metadata;

[0072] Step S504: completing the link connection of each decision node based on the logic trend to obtain a function set, wherein the checkpoint is set between every two function sets, and the function set includes a plurality of meta-functions;

[0073] Step S506: Obtain the constructed business decision graph based on the initial node, the end node, the function set, and the checkpoint.

[0074] It should be noted that, in this embodiment, the metadata mainly includes meta-functions. Accordingly, the metadata described in this application also includes initial nodes, end nodes, checkpoints, decision nodes, and, when applied, the decision nodes include at least serial decision nodes, parallel decision nodes, weighted routing decision nodes, and failure routing decision nodes. Therefore, after obtaining the basic data, the link connection of each decision node can be completed based on the metadata and the corresponding logical direction to obtain the corresponding function set, that is, to complete a decision tree, and then combine the corresponding initial node, the end node, the function set and the checkpoint to obtain the constructed business decision graph, wherein the checkpoint is set between every two function sets. Since the function set corresponds to a decision tree, the decision tree naturally includes several of the meta-functions.

[0075] Furthermore, in one embodiment of the invention, Figure 6 As shown, it shows an application flow chart of the business decision diagram for business scenario access, in which, first, you need to configure the business scenario and save the business scenario information, and then choose to automatically generate a decision diagram (create an initialization decision diagram) or copy the existing decision diagram, and then according to the created decision nodes, combine the meta-function integration function in the meta-function list to obtain the function set, connect the nodes according to the logical direction, create a process relationship, and simultaneously set corresponding checkpoints between the function sets, and set the final end node to save the current rule version as a business decision diagram.

[0076] Furthermore, in one embodiment of the invention, Figure 7 As shown, the method further includes the following steps:

[0077] Step S702: updating metadata in the business decision graph based on the basic data;

[0078] Step S704, determining whether the current metadata exists in the business decision graph;

[0079] Step S706: If it does not exist, the newly added metadata is added as a new meta-function combined with the corresponding logical direction to the corresponding function set;

[0080] Step S708, if existing, data updating of the old version of the meta function based on the newly added metadata to replace the old version of the meta function.

[0081] It should be noted that in the present embodiment, since the minimum unit of the business decision graph is the meta function, in actual application, the meta data needs to be updated, specifically, the meta data in the business decision graph is updated based on the basic data, and it is specifically judged whether the current meta data exists in the business decision graph, wherein if not, the newly added meta data is added to the corresponding function set as a new meta function combined with the corresponding logical direction, and if existing, data updating of the old version of the meta function based on the newly added metadata to replace the old version of the meta function.

[0082] Specifically, as shown in Figure 8 the application flowchart of the meta function maintenance is displayed, the meta data is distinguished, wherein for the newly added meta function, it needs to be added online to the meta function list, and for the one needing to be updated, offline processing is performed, and the blood relationship of the decision node is specifically judged, and the updated meta function is added in the same way as the new function to perform updating.

[0083] The application embodiment further provides a flow transfer scheduling control system based on a rule decision graph, which can implement the flow transfer scheduling control method based on the rule decision graph. However, the implementation device of the flow transfer scheduling control method based on the rule decision graph includes but is not limited to the structure of the flow transfer scheduling control system based on the rule decision graph listed in the present embodiment, and any structural deformation and substitution of the prior art according to the principle of the present application is included in the protection scope of the present application.

[0084] Please refer to Figure 9 In an embodiment, the present embodiment provides a flow transfer scheduling control system 90 based on a rule decision graph, and the system includes:

[0085] The acquisition module 91 is configured to acquire a service request of a user terminal, wherein a business scenario code is identified based on the service request;

[0086] The processing module 92 is configured to process the service request by using the constructed business decision graph to obtain a processing result, wherein a function set in the business decision graph is result judged based on the business scenario code;

[0087] The feedback module 93 is configured to feed back the processing result to the user terminal, wherein the processing result includes at least one end result, and the end result corresponds to a checkpoint or an end node in the business decision graph.

[0088] Since the specific implementation of this embodiment corresponds to the aforementioned method embodiment, the same details will not be repeated here, and those skilled in the art should also understand that Figure 9 The division of the various modules in the embodiment is merely a division of logical functions. In actual implementation, all or part of the modules can be integrated into one or more physical entities, and all of these modules can be implemented in the form of software called by processing elements, or all of them can be implemented in the form of hardware. Some modules can also be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware.

[0089] See Figure 10 This embodiment provides an electronic device. Specifically, the electronic device includes at least: a memory and a processor connected via a bus, wherein the memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to perform all or part of the steps in the aforementioned method embodiment.

[0090] In summary, the present invention innovatively implements flexible process orchestration and function scheduling through platform integration and link calling. By configuring the rule set, it can automatically trigger corresponding operations according to different conditions and requirements, solve the problem of flexible and real-time configuration of rules for function combination under complex business conditions, improve the efficiency of the system, and reduce the difficulty of complex business logic processing.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices or methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules / units is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules or units, which can be electrical, mechanical or other forms.

[0092] The modules / units described as separate components may or may not be physically separate, and the components displayed as modules / units may or may not be physical modules, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules / units may be selected according to actual needs to achieve the purpose of the embodiments of the present application. For example, the functional modules / units in the various embodiments of the present application may be integrated into a processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into a single module / unit.

[0093] Those skilled in the art should further understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in the foregoing description in a general manner. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0094] The embodiments of the present application also provide a computer readable storage medium. Those skilled in the art can understand that all or part of the steps of the methods described above can be completed by a processor instructed by a program, and the program can be stored in a computer readable storage medium. The storage medium is a non-transitory medium, such as a random access memory, a read-only memory, a flash memory, a hard disk, a solid state disk, a magnetic tape, a floppy disk, an optical disc and any combination thereof. The storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center and the like integrated with one or more available medium sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a digital video disc (DVD)) or a semiconductor medium (for example, a solid state disk (SSD)) and the like.

[0095] The embodiments of the present application can also provide a computer program product, which includes one or more computer instructions. When the computer instructions are loaded and executed on a computing device, all or part of the processes or functions described in the embodiments of the present application are generated. The computer instructions can be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions can be transmitted from one website, computer or data center to another website, computer or data center through wired (for example, coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (for example, infrared, wireless, microwave and the like) mode.

[0096] The computer program product is executed by a computer, and the computer executes the method described in the foregoing method embodiments. The computer program product can be a software installation package, and when the foregoing method needs to be used, the computer program product can be downloaded and executed on the computer.

[0097] The descriptions of the processes or structures corresponding to the above figures have different emphases. For parts that are not described in detail in a certain process or structure, please refer to the relevant descriptions of other processes or structures.

[0098] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical concepts disclosed in this application shall be covered by the claims of this application.

Claims

1. A flow scheduling control method based on rule decision diagram, characterized in that: include: Obtaining a service request from a user terminal, wherein a service scenario code is obtained based on the service request identification; Processing the business request using the constructed business decision graph to obtain a processing result, wherein a result judgment is performed on the function set in the business decision graph based on the business scenario code; Feedback the processing result to the user end, wherein the processing result includes at least one end result, and the end result corresponds to a checkpoint or an end node in the business decision graph.

2. The flow scheduling control method based on rule decision diagram according to claim 1 is characterized in that: The method further includes constructing the business decision diagram, specifically comprising: Obtaining input basic data, wherein the basic data at least includes metadata, logical direction, and business scenario code; Creating an initialization decision graph, wherein the initialization decision graph includes at least two decision trees; The business decision graph is obtained by connecting the initialization decision graph based on the basic data.

3. The flow scheduling control method based on rule decision diagram according to claim 2 is characterized in that: The connecting process of the initialization decision graph based on the basic data to obtain the business decision graph specifically includes: identifying an initial node, an end node, a checkpoint, a decision node, and a meta-function based on the metadata; Based on the logic trend, a link connection is completed for each decision node to obtain a function set, wherein the checkpoint is set between every two function sets, and the function set includes a plurality of meta-functions; The constructed business decision graph is obtained based on the initial node, the end node, the function set and the checkpoint, wherein the decision nodes at least include serial decision nodes, parallel decision nodes, weighted routing decision nodes and failed routing decision nodes.

4. The flow scheduling control method based on rule decision diagram according to claim 3 is characterized in that: The method further comprises: The metadata in the business decision diagram is updated based on the basic data, wherein: Determine whether the current metadata exists in the business decision graph, where: If it does not exist, the newly added metadata is added as a new meta-function combined with the corresponding logical direction to the corresponding function set; If it exists, the old version of the meta-function is updated based on the newly added metadata to replace the old version of the meta-function.

5. The flow scheduling control method based on rule decision diagram according to claim 1 is characterized in that: Obtaining the business scenario code based on the business request identification specifically includes: performing data processing based on the business request input by the user end to obtain the business scenario code, which at least includes performing text recognition on the business request to obtain a request recognition result, and matching a preset scenario code library based on the request recognition result to obtain the business scenario code.

6. The flow scheduling control method based on rule decision diagram according to claim 5 is characterized in that: The process of processing the business request using the constructed business decision graph to obtain a processing result specifically includes: Matching the business decision diagram based on the business scenario code corresponding to the business request to obtain a corresponding preset function set; The processing result is obtained by performing a logical judgment on the business request based on the meta-function in the preset function set, including outputting the processing result based on the detection result of the checkpoint, or outputting the processing result based on the detection result of the end node.

7. The flow scheduling control method based on rule decision diagram according to claim 6 is characterized in that: The matching of the business decision diagram with the business scenario code corresponding to the business request to obtain the corresponding preset function set specifically includes: loading a function engine to capture the output of the meta-function under the current business scenario and the judgment of the gate logic to obtain the corresponding meta-function to be executed as the preset function set.

8. A flow scheduling control system based on rule decision diagram, characterized in that: include: An acquisition module, configured to acquire a service request from a user terminal, wherein a service scenario code is obtained based on identification of the service request; a processing module, configured to process the business request using the constructed business decision graph to obtain a processing result, wherein a result judgment is performed on the function set in the business decision graph based on the business scenario code; A feedback module is used to feed back the processing result to the user end, wherein the processing result includes at least one end result, and the end result corresponds to a checkpoint or end node in the business decision graph.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the flow scheduling control method based on the rule decision diagram described in any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: The electronic device includes: a processor and a memory; wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the flow scheduling control method based on the rule decision diagram as described in any one of claims 1 to 7.

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