Business process automatic processing method and device based on low-code platform

Abstract

The application discloses a business process automatic processing method and device based on a low-code platform, comprising: determining a target business; selecting a process editing template corresponding to the target business according to the target business, wherein the process editing template is generated by a trained process modeling model, and the process editing template provides an interface of process information of a business system associated with the target business; receiving a calling instruction for the interface of process information in the process editing template; determining business process information of the target business; and executing a business process of the target business according to the business process information of the target business. Thus, the automation level of the business process is improved, the process design and maintenance cost is reduced, and the enterprise operation efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of software, in particular to a business process automatic processing method and device based on a low-code platform. BACKGROUND

[0002] In the wave of digital transformation, especially the rapid arrival of the artificial intelligence era, enterprises have an increasing demand for business process automation and intelligentization.

[0003] A related technology proposes an RPA process intelligent optimization method based on a large model, which accurately identifies bottlenecks and optimization points by deeply analyzing the process, effectively improving optimization efficiency and quality, and enhancing process adaptability. Another related technology converts business requirements into executable code through natural language understanding, greatly reducing the technical threshold of process design. However, both focus on optimizing the process itself, but do not address the automation level, integration level, and flexibility of the process. Based on this, how to improve the automation and intelligentization of business processes, the integration and flexibility of business processes, to meet the intelligent office requirements of enterprises and improve the operational efficiency of enterprises has become a technical problem to be solved. SUMMARY

[0004] Therefore, the main purpose of the present application is to provide a business process automation method and device based on a low-code platform, aiming to realize more flexible, efficient and intelligent business process automation to meet the high requirements of enterprise-level applications for process automation and intelligentization.

[0005] To achieve the above-mentioned purpose, the technical scheme of the present application is as follows:

[0006] The embodiment of the present application provides a business process automatic processing method based on a low-code platform, which comprises the following steps:

[0007] determining a target business;

[0008] According to the target business, a process editing template corresponding to the target business is selected, the process editing template is generated by a trained process modeling model, and the process editing template provides an interface of process information of a business system associated with the target business;

[0009] receiving a calling instruction for the interface of the process information in the process editing template; determining the business process information of the target business;

[0010] According to the business process information of the target business, the business process of the target business is executed.

[0011] In the above-mentioned scheme, the method further comprises:

[0012] monitoring the business process and recording the execution process information of the business process;

[0013] The method further includes:

[0014] According to the target service, a first process editing template corresponding to the target service is selected.

[0015] According to the execution process information, it is determined whether the first process editing template meets the execution condition.

[0016] In response to the first process editing template meeting the execution condition, the first process editing template is used as the process editing template.

[0017] The method further includes:

[0018] In response to the first process editing template not meeting the execution condition, the first process editing template is adjusted to a second process editing template meeting the execution condition according to the execution process information, and the second process editing template is used as the process editing template.

[0019] The method further includes:

[0020] The business process is monitored, and execution result information of the business process is recorded.

[0021] The second process editing template is input into a process modeling model as a template sample of the target service and / or the execution result, so as to train the process modeling model.

[0022] The method further includes:

[0023] According to the target service, interface information of the target service is determined by using an interface calling model for the target service.

[0024] The method further includes:

[0025] According to the interface information, an interface for the process information in the process editing template is determined.

[0026] According to the interface for the process information, a calling instruction for the interface for the process information in the process editing template is generated.

[0027] According to the calling instruction, the interface is called and the business process information of the target service is determined.

[0028] The method further includes:

[0029] A trigger condition for the target service is monitored, and the trigger condition includes at least one of the following: a judgment condition, an exception handling condition, and an action trigger condition.

[0030] According to the trigger condition, a target service corresponding to the trigger condition is determined.

[0031] In the above scheme, the process modeling model comprises an entity model of a business entity, a business logic model, a decision model and an appearance model.

[0032] According to the target service, a process editing template corresponding to the target service is selected, comprising:

[0033] According to the target service, a business entity of the target service is defined by using the entity model of the business entity.

[0034] According to the target service, an interaction relationship of the business entity of the target service is defined by using the business logic model in a visual connection manner.

[0035] According to the target service, a decision condition of a business planning engine of the target service is configured by using the decision model.

[0036] According to the target service, a business interaction interface of the target service is generated by using the appearance model.

[0037] According to the business entity, the interaction relationship of the business entity, the decision condition of the business rule engine and the business interaction interface, a process editing template is constructed.

[0038] In addition, the embodiment of the present application also provides a business process automatic processing device based on a low-code platform, the device comprises:

[0039] A first determination module is configured to determine a target service.

[0040] A selection module is configured to select a process editing template corresponding to the target service according to the target service, wherein the process editing template is generated by a trained process modeling model, and the process editing template provides an interface of process information of a business system associated with the target service.

[0041] A second determination module is configured to receive a calling instruction for the interface of the process information in the process editing template, and determine business process information of the target service.

[0042] An execution module is configured to execute a business process of the target service according to the business process information of the target service.

[0043] To achieve the above object, the embodiment of the present application also provides a computing device, which comprises:

[0044] A processor;

[0045] A memory for storing processor-executable instructions; wherein the processor is configured to execute the business process automatic processing method based on a low-code platform according to any of the above schemes.

[0046] To achieve the above object, the embodiment of the present application further provides a computer storage medium, comprising: a computer storage medium storing one or more programs, which can be executed by one or more processors to enable the one or more processors to execute the low-code platform-based business process automatic processing method according to any one of the above solutions.

[0047] The low-code platform-based business process automatic processing method and device provided by the embodiment of the present application can automatically generate a process editing template matched with a target business through a trained process modeling model, so that a non-technical user can directly call the template interface without designing process logic from scratch and without using code to set the process by a technical personnel. Meanwhile, the embodiment of the present application directly provides a business process through the process editing template provided by the process modeling model, so that the interface of the process information that needs to be called can be determined for the process editing template, and the business process information of the target business is generated after the interface is called, so that the obtained business process information can be more accurate and more flexible. In addition, the process editing template can call the interface of the process information of each system, so that the data of each system can be better aggregated, and the information fragmentation phenomenon between each system of an enterprise can be reduced. In summary, the embodiment of the present application obtains the process editing template based on the target business through the trained process modeling model, and obtains the process information of the target business through the interface of each system provided in the process editing template, and automatically executes the business process of the target business based on the process information, so as to solve the problems of the prior art, such as the need for technical personnel to configure the process in the background, low development efficiency, strong professionalism, low intelligence and automation of the process, and low integration degree of the process, and realize more flexible, efficient, intelligent, and highly integrated business process automation, so as to meet the high requirements of enterprise-level applications for process automation and intelligence. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 A process schematic diagram of the low-code platform-based business process automatic processing method provided by some embodiments of the present application is shown in FIG. 1.

[0049] Figure 2 Another process schematic diagram of the low-code platform-based business process automatic processing method provided by some embodiments of the present application is shown in FIG. 2.

[0050] Figure 3 A flow modeling model architecture schematic diagram provided for some embodiments of the present application;

[0051] Figure 4 A component structure schematic diagram of a business process automatic processing device based on a low-code platform provided for some embodiments of the present application;

[0052] Figure 5 A hardware structure schematic diagram of a computing device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0053] Embodiments of the present application aim to obtain a process editing template based on a target business through a trained flow modeling model, and automatically execute a business process, so as to solve the problems in the prior art, realize intelligentization and automation of the process, improve process integration, reduce dependence on technical personnel, and improve enterprise operation efficiency.

[0054] The embodiments of the present application will be described in detail below with reference to the accompanying drawings, so that the advantages and features of the present application can be more easily understood by those skilled in the art, and the protection scope of the present application can be more clearly defined.

[0055] Figure 1 A flow schematic diagram of a business process automatic processing method based on a low-code platform provided for some embodiments of the present application, as shown in Figure 1 The embodiments of the present application provide a business process automatic processing method based on a low-code platform, applied to a computing device, and the method comprises the following steps:

[0056] Step 101: determining a target business;

[0057] The computing device herein can be a terminal device, and the terminal device herein can be a fixed terminal or a mobile terminal. The fixed terminal can be a desktop computer or an all-in-one machine, and the mobile terminal can be a notebook computer, a tablet computer or a mobile phone, etc. In some embodiments, the computing device herein can be a computing device within a certain application range, such as a computing device for office use of a certain company, etc. The computing device can be used to run and manage a business process system of an enterprise.

[0058] In some embodiments, step 101, i.e., determining a target business, can comprise: selecting a business type to be processed, such as an order approval process or a reimbursement process, through a visual interface of a low-code platform; and the computing device automatically identifies a target business scenario according to a business label selected by a user, so as to determine the target business. The target business herein can include a business label, a business type or a business identifier, etc. Any information capable of representing the target business is included.

[0059] To make the business process system more automated and intelligent, in some embodiments, the step 101, i.e., the determining the target business, can include:

[0060] detecting a trigger condition for the target business, the trigger condition including at least one of: a judgment condition, an exception handling condition, and an action trigger condition;

[0061] determining the target business corresponding to the trigger condition according to the trigger condition.

[0062] It should be noted that the business process system is integrated with a trigger condition detection system, which includes: an event collection module for real-time capturing of original signals from the business process system, user terminals and Internet of Things devices. It should be noted that the Internet of Things devices refer to entity information within an enterprise monitored by the business process system, such as warehouse information, etc.; a condition classification module connected to the event collection module and configured to classify the original signals into: judgment condition signals, exception handling condition signals, and action trigger condition signals; a business mapping engine for determining the target business according to the classification results.

[0063] Specifically, the judgment condition detection includes:

[0064] The rule engine in the business mapping engine loads a preset business rule set, which includes: threshold rules, such as inventory quantity less than a safe inventory threshold; logic rules, such as foreign currency amount in contract type greater than a predetermined value; time sequence rules, such as continuous N-day sales decline greater than a preset amplitude value; for example, in the case of inventory quantity less than the safe inventory, the replenishment process can be triggered; in the case of foreign currency amount in contract type greater than the predetermined value, the legal review process can be triggered; in the case of continuous three-day sales decline of 20%, the promotion scheme approval process can be triggered.

[0065] Real-time comparison of business data flow and rule set;

[0066] When the data flow characteristics match the rules, a judgment condition signal is generated and a rule identifier is attached.

[0067] Specifically, the exception handling condition detection includes:

[0068] An exception capture matrix is established, such as Table 1:

[0069] Table 1

[0070] When an exception is detected, a root cause analysis submodule is started, which specifically includes:

[0071] Extracting an exception feature vector, such as at least one of an error code, a timestamp, and an impact range;

[0072] Retrieving similar cases in the historical case library;

[0073] Outputting an exception handling suggestion, where the exception handling suggestion includes a data repair process, or an exception check process, etc.

[0074] Specifically, the action trigger condition detection includes:

[0075] Deploying multi-source action sensors, including at least one of:

[0076] A UI (User Interface) event listener for capturing a button click coordinate sequence;

[0077] An API (Application Programming Interface) call monitor for recording endpoint access patterns;

[0078] An Internet of Things signal receiver for parsing, for example, MQTT (Message Queuing Telemetry Transport) protocol packets.

[0079] Analyzing the action sketch through a semantic analysis module, including at least one of:

[0080] Converting the original action into a standardized operation instruction;

[0081] Using a BERT (Bidirectional Encoder Representation from Transformers) model to identify operation semantics, such as crisis response semantics for emergency start;

[0082] Generating an action label with a confidence score.

[0083] In some embodiments, according to the trigger condition, the target business corresponding to the trigger condition is determined, including: determining the target business through a business mapping engine.

[0084] Specifically, the determination of the target business through the business engine includes at least one of:

[0085] When a single condition signal is received, the target business can be determined by querying a condition-business mapping table.

[0086] Here, the condition-business mapping table can be as shown in Table 2:

[0087] Condition type Condition characteristic example Map target business Judgment condition Inventory less than 100 Replenishment flow Exception condition Payment gateway timeout Payment failure handling flow Action condition Emergency button trigger Crisis response flow

[0088] Table 2

[0089] When receiving the multi-condition signal, the correlation analysis submodule is started, and specifically includes the following:

[0090] The Flink (open source distributed computing framework) complex event processing (CEP, Customer Engagement Platform) engine is used to detect condition combinations;

[0091] The decision logic is executed, for example, when "insufficient inventory" and "abnormal supplier" are met at the same time, triggering the "backup supplier selection process";

[0092] The target business identification and execution priority parameters are output.

[0093] In this way, by establishing multi-dimensional trigger conditions to determine the target business, manual intervention can be reduced, and the automation and intelligent degree of the business process system can be improved, so that the business process system can support automatic handling of complex condition combinations, and provide a strong guarantee for meeting the intelligent office requirements of enterprises and improving the operation efficiency of enterprises.

[0094] Further, in some embodiments, in order to improve the detection accuracy of the trigger condition, on the one hand: the historical business data flow is periodically analyzed by an LSTM (long short-term memory) model; the rule threshold is periodically calibrated; and the rule confidence weight is periodically updated. On the other hand, when the condition matching conflicts, an NLP (Neuro-Linguistic Programming) module is called to analyze the correlation documents, such as SOP manuals, to generate handling suggestions and request manual confirmation, and record the decision path for model retraining. In this way, the use of the model to judge the trigger condition can be more accurate.

[0095] Step 102: According to the target business, a process editing template corresponding to the target business is selected, the process editing template being generated by a trained process modeling model, and the process editing template providing an interface of process information of a business system associated with the target business.

[0096] It should be noted that in some embodiments, the method further includes a process modeling model construction method.

[0097] Specifically, the process modeling model is trained and generated by the following steps:

[0098] In the data preparation phase, the method comprises: collecting historical business process data sets, including: BPMN (Business Process Modeling Notation) process diagram files recorded by the business process execution engine, business node execution logs, and cross-system interface call records; structuring the collected data, and performing the following steps through an ETL pipeline: a) parsing the boundary events and gateway nodes in the BPMN file, extracting the node relationship topology; b) matching the WSDL (Web Services Description Language) service description file, and associating the service breakpoints corresponding to each node; c) generating a knowledge graph triple structure, which can be in the format of source node, relationship type, target node, and interface identifier.

[0099] In the model training phase, the method comprises: constructing a graph neural network architecture, which comprises: i) an input layer that receives a business node feature vector with a dimension of 256; ii) three layers of GraphSAGE (Graph Sample and aggregate) convolution layers, using a ReLU (Rectified Linear Unit) activation function; iii) an output layer that generates a process template code stream in Protobuf format; configuring training parameters: 1) using a cross-entropy loss function with weight adjustment, setting a 3 times weight system for rare business scenarios with an occurrence frequency of less than 5%; 2) using an AdamW (Adaptive Moment Estimation with Weight Decay) optimizer with an initial learning rate of 0.001 and an exponential decay rate of 0.95; 3) setting 200 training cycles, and triggering an early stopping mechanism when the validation set loss does not decrease for 5 consecutive times.

[0100] In this way, the three-layer GraphSAGE convolution layer models the complex gateway relationship, realizes higher node path recognition accuracy, and solves the problem of parallel branch structure distortion; the interface binding mechanism based on the knowledge graph triple achieves higher cross-system interface automatic matching rate, compresses the configuration time to a shorter time, and eliminates the risk of process interruption caused by human errors; the loss function with weight adjustment improves the success rate of low-frequency business template generation, reduces resource consumption, and supports full-scene intelligent coverage of industrial complex businesses.

[0101] Here, in step 102, the generation mechanism of the process editing template is:

[0102] The target business feature vector is input into the trained process modeling model, and the model output includes:

[0103] Node topology, explicitly sequential flow and parallel gateway relationship;

[0104] Pre-bound business system interface, including interface path and call parameters;

[0105] Exception handling path, defining timeout retry strategy and failure fallback scheme;

[0106] The generated template adopts XML structured description, and an example is as follows:

[0107] XML

[0108] <template id="PO_Approval">

[0109] <nodes>

[0110] <node id="1" type="审批" system="CRM" interface="approval_api" / >

[0111] <node id="2" type="支付" system="ERP" interface="payment_api" retry_policy="3x" / >

[0112] < / nodes>

[0113] <edges>

[0114] <edge source="1" target="2" condition="status=APPROVED" / >

[0115] < / edges>

[0116] < / template>

[0117] Further, the process editing template generated by the trained process modeling model can be saved in the template library. Illustratively, a MongoDB (MongoDB Database, a database based on distributed file storage) shard cluster is used for distributed storage; a multi-dimensional index system is established.

[0118] Specifically, the multi-dimensional index system can include at least one of the following: a business_domain field creates a hash index, supporting quick retrieval by business domain; a node_count field creates a range index, enabling filtering by process complexity; and an update_time field creates a TTL index, automatically cleaning templates that have not been accessed for 90 days.

[0119] In this way, the query efficiency, storage scalability and operation and maintenance automation level of the process template library are improved, which is especially suitable for large-scale, high-concurrency enterprise-level process management systems. At the same time, through the design of multi-dimensional indexes, the business demand is accurately matched, and the long-term maintenance cost is reduced.

[0120] In some embodiments, the step 102, i.e., the selection of the process editing template corresponding to the target business according to the target business, can further include:

[0121] A multi-level matching engine is used for selection, specifically including:

[0122] Primary screening, i.e., performing a query in the template library according to the target business tag; using an inverted index technology to recall the top 50 candidate templates with the highest similarity;

[0123] Precision matching, i.e., calculating a comprehensive similarity score, accelerating the calculation through a Faiss vector retrieval engine, and determining that the response time is less than a preset time, e.g., 10 milliseconds. The similarity score here can be the product of the node topology similarity and the node topology similarity weight, plus the product of the system interface coverage and the system interface coverage weight, plus the product of the historical execution success rate and the historical execution success rate weight;

[0124] Intelligent recommendation, that is, when the highest similarity gets lower than a preset score value, a process modeling model is invoked to generate a new template in real time; the generated new template is stored in a template library and a template identifier is returned.

[0125] In this way, the embodiment realizes accurate matching, intelligent recommendation and adaptive expansion of the process template, and significantly improves the process selection accuracy in a complex business scenario.

[0126] It should be understood that the process editing template can provide a business system interface in the following manner:

[0127] The interface description layer uses OpenAPI 3.0 specification to describe the interface metadata, including: (a) interface path and HTTP method; (b) request parameter mode definition; (c) response data structure specification;

[0128] An example description fragment is as follows:

[0129] Yaml

[0130] / inventory-check:

[0131] get:

[0132] parameters:

[0133] name: product_id

[0134] in: query

[0135] schema: {type: string}

[0136] responses: 200:

[0138] content:

[0139] application / json:

[0140] schema: {stock: integer}

[0141] Runtime binding mechanism:

[0142] When a user drags a template node to a visual designer, the interface description metadata is automatically parsed;

[0143] The business system actual endpoint address is queried through a service discovery component;

[0144] The interface adaptation code is dynamically generated, and an example is as follows:

[0145] Java

[0146] @Invoke(path=" / approval_api", system="CRM")

[0147] public class CRMApprovalProxy {

[0148] public Response execute(Request req) {

[0149] return FeignClientFactory.create(CRM.class).submit(req)

[0150] }

[0151] }

[0152] Thus, compared with the traditional way, the template matching is accurately improved, the interface configuration time is shortened, the efficiency is improved, and the coverage of cross-system exception handling is improved, supporting automatic processing of various exceptions, inventory verification failure and the like.

[0153] Step 103: receiving a calling instruction for an interface of process information in the process editing template, and determining the business process information of the target business.

[0154] It should be understood that a drag operation of the interface of the process information in the process editing template is received through a visual interface, and the drag operation is used to call the interface of the process information. For example, when the "payment verification" node in the process editing template is dragged, the interface bound thereto will call the related data of the payment system, and the payment verification process in the payment system is called. Specifically, a specific Java method is generated, which calls the RESTful service of the payment system through the Feign client. For example, when the "purchase audit" node in the process template is dragged, the interface bound thereto will call the purchase audit process of the purchase system to determine the business process information of the purchase audit link in the target business.

[0155] Thus, the business information node is directly dragged through the visual arrangement, the "plug and play" integration of enterprise-level system resources is realized, the business process arrangement efficiency is higher, and the reliability and consistency of the system call are also guaranteed.

[0156] Step 104: executing the business process of the target business according to the business process information of the target business.

[0157] For example, the execution of the business process of the target business according to the business process information of the target business can include:

[0158] The system parses business process information such as a BPMN model and a JSON process definition, automatically disassembles the information into executable task units, and dynamically allocates execution nodes through a distributed task scheduling engine such as XXL-JOB and Apache Airflow to ensure high throughput and low latency.

[0159] In some embodiments, to improve resource utilization of the system, the business process of the target business can include at least one of the following:

[0160] Serial execution, for example, "payment verification" is successful, and then "purchase audit" is triggered, which is suitable for processes with strong dependency relationships;

[0161] Parallel execution, for example, "inventory check" and "credit evaluation" are executed simultaneously, and exemplarily, independent services are concurrently called using a Fork-Join model;

[0162] Conditional branching execution, for example, whether to enter manual audit is determined according to the order amount, and exemplarily, a rule engine is used to dynamically select an execution path.

[0163] In this way, the embodiment of the application can automatically generate a process editing template matched with the target business through the trained process modeling model, so that non-technical users can also directly call the template interface without designing process logic from scratch, and technical personnel do not need to use code to set the process; at the same time, the embodiment of the application directly provides a business process through the process editing template, so that the interface of the process information to be called can be determined for the process editing template, the target business process information is generated after the interface is called, so that the obtained business process information is more accurate and has higher flexibility; in addition, the process editing template can call the interfaces of the process information of each system, so that the data of each system can be better aggregated, and the information fragmentation phenomenon between the systems of the enterprise is reduced. In summary, through the embodiment of the application, the process editing template is obtained based on the target business through the trained process modeling model, the process information of the target business is obtained based on the interfaces of each system provided in the process editing template, and the business process of the target business is automatically executed based on the process information, so as to solve the problems in the prior art that technical personnel need to configure the process in the background, the development efficiency is low, the professional is strong, the process is not intelligent and automatic, and the process integration degree is low, realize more flexible, efficient, intelligent, and high-integration-degree business process automation, and meet the high requirements of enterprise-level applications for process automation and intelligence.

[0164] In some embodiments, Figure 2 Another flowchart of the business process automatic processing method based on the low-code platform provided by some embodiments of the application is shown in Figure 2 The method further includes:

[0165] Step 201: monitoring the business process and recording execution process information of the business process;

[0166] The step 102, i.e., selecting a process editing template corresponding to the target business according to the target business, comprises:

[0167] Step 1021: selecting a first process editing template corresponding to the target business according to the target business;

[0168] Step 1022: determining whether the first process editing template meets an execution condition according to the execution process information;

[0169] Step 1023: in response to the first process editing template meeting the execution condition, taking the first process editing template as the process editing template.

[0170] Exemplarily, in some embodiments, the step 201 of monitoring the business process and recording the execution process information of the business process can be monitored by a way of burying points, for example, embedding a lightweight Agent agent at a business process node such as approval, data conversion, API calling, and collecting execution logs in real time, wherein the execution logs include time consumption, success rate, input / output data snapshot, etc.; and the execution process information is generated by an event stream processing method.

[0171] Exemplarily, the execution process information is generated by an event stream processing method, which comprises: collecting events by a message queue such as Kafka or Pulsar, and using Flink / Spark Streaming for real-time aggregation to generate the execution process information.

[0172] The execution condition can include, but is not limited to, a hard condition and a soft condition, wherein the hard condition can include a compliance condition, for example, the first process editing template contains a “direct payment to supplier” node, and the latest financial policy requires “three-party price comparison before payment” in the execution process information, so the first process editing template does not meet the execution condition, and a new process editing template needs to be replaced. The soft condition can include a performance condition, for example, the first process editing template presets “IT fault handling needs to be responded within 2 hours”, and the actual median of the corresponding time is 3 hours in the execution process information, so the first process editing template does not meet the execution condition.

[0173] In some embodiments, the method further comprises:

[0174] Step 1024: in response to the first process editing template not meeting the execution condition, adjusting the first process editing template to a second process editing template meeting the execution condition according to the execution process information, and taking the second process editing template as the process editing template.

[0175] Exemplarily, adjusting the first process editing template to the second process editing template satisfying the execution condition according to the execution process information can include: replacing the first process editing template with a backup process editing template according to the execution process information. Exemplarily, if the execution condition is not satisfied, a template replacement instruction can be automatically triggered to perform the template replacement. In the above scenario, if the compliance condition is not satisfied, a process editing template with, for example, a comparison node is automatically replaced; if the performance condition is not satisfied, for example, the median of the IT fault response time is 3 hours, which exceeds 2 hours, a process editing template with, for example, “upgrade to an expert team” is recommended to be enabled.

[0176] Thus, the embodiment can dynamically switch the process editing template of the subsequent process by monitoring the execution process of the business process, so as to ensure that the process editing template always matches the business status, guarantee the effective execution of the business process, and reduce the process risk operation and eliminate the inefficient template, and reduce the manual analysis cost. Based on this, the embodiment can dynamically adjust the process editing template based on the execution process information of the business process, and in the case that the current process editing template of the business process does not satisfy the execution condition, the static process management can be upgraded to intelligent dynamic process management, further improving the automation and intelligence of the business process, and further meeting the high requirements of enterprise-level applications on process automation and intelligence.

[0177] In some embodiments, the method further comprises:

[0178] monitoring the business process and recording execution result information of the business process;

[0179] inputting the second process editing template as a template sample and / or execution result of the target business into the process modeling model for training the process modeling model.

[0180] It can be understood that the execution result information herein can include a comprehensive data set generated after the business process runs, and can include the following:

[0181] an identifier of the process instance, used to identify the number of single process execution;

[0182] a final state, such as success, failure, interruption, or timeout, etc.;

[0183] a start / end timestamp.

[0184] If the execution result information of the business process is recorded, the process success rate can be calculated for the evaluation of the overall monitoring degree of the business process system and the subsequent resource optimization allocation, etc.

[0185] In some embodiments, the second process editing template is input into the process modeling model as a template sample of the target business and / or execution result information for training the process modeling model. It can be understood that the training of the process modeling model includes: selecting a plurality of historical determined process editing templates and execution result information marked with a success rate reaching a success rate threshold, i.e., valid execution result information, from the execution result information as learning samples, and continuing to train the process modeling model, so that the process editing template generated by using the new process modeling model can reduce the generation of historical defects and improve the accuracy of the business process obtained by using the process editing template.

[0186] In this way, the embodiment changes the static process management into an intelligent system of continuous learning and dynamic optimization, further improves the automation and intelligentization of the business process, and further meets the high requirements of enterprise-level applications on process automation and intelligentization.

[0187] In some embodiments, the method further includes:

[0188] According to the target business, the interface calling model for the target business is used to determine the interface information of the target business;

[0189] The step 103, i.e., receiving the calling instruction of the interface for the process information in the process editing template, determines the business process information of the target business, including:

[0190] According to the interface information, the interface for the process information in the process editing template is determined;

[0191] According to the interface of the process information, the calling instruction of the interface for the process information in the process editing template is generated;

[0192] According to the calling instruction, the interface is called and the business process information of the target business is determined.

[0193] It can be understood that the interface calling model here is an algorithm model specially used for intelligent identification, matching and calling of the interface of the business process system, and the core function thereof is to automatically determine the interface to be called and its parameter configuration according to the demand of the target business.

[0194] In the embodiment, the interface information to be called by the target business is automatically determined by using the interface calling model, and the calling instruction is directly generated according to the interface information, without manual visual editing and manual participation. For employees who are new to the target business, process system training is not required, which improves the execution efficiency of the business process, and also enables the business process system to be more automated and intelligent.

[0195] In some embodiments, please refer to Figure 3 As Figure 3As shown, the flow modeling model can include: an entity model 31 of business entities, a business logic model 32, a decision model 33, and an appearance model 34;

[0196] According to the target business, a flow editing template corresponding to the target business is selected, including:

[0197] According to the target business, the entity model 31 of business entities is used to define the business entities of the target business;

[0198] According to the target business, the business logic model 32 is used to define the interaction relationship of the business entities of the target business by a visual connection method;

[0199] According to the target business, the decision model 33 is used to configure the decision conditions of the business planning engine of the target business;

[0200] According to the target business, the appearance model 34 is used to generate the business interaction interface of the target business;

[0201] According to the business entities, the interaction relationship of the business entities, the decision conditions of the business rule engine, and the business interaction interface, a flow editing template is constructed.

[0202] The business entities herein can include but are not limited to actual process objects or concepts, such as customer, product, and order information. In actual applications, the business entities include attributes and behaviors. The attributes refer to structured fields, such as order amount and supplier credit rating. The behaviors refer to associated operation methods, such as total amount.

[0203] Exemplarily, the business logic model 32 is used to define the interaction relationship of the business entities of the target business by a visual connection method, which can be, by providing a low-code flowchart editor, by receiving a user's drag operation on a node, defining the interaction relationship between the business entities, such as the interaction of data conversion, notification, and approval in financial approval.

[0204] In some embodiments, the decision model can automatically adjust the rule threshold according to market fluctuations. Thus, the dynamic optimization of the business process system is realized, and a strong guarantee is provided for the intelligentization and automation of the business process system.

[0205] In some embodiments, the appearance model can dynamically render the interface according to the user's role and device type, thereby facilitating the user's consistent experience and reducing the training cost.

[0206] In this embodiment, the process modeling model is learned and trained and applied by being divided into four models respectively, which is beneficial to the accuracy of the process editing template generated by the process modeling model, and through the cooperation of multiple models, the process design can be changed from 'code development' to'model-driven' more intelligent and automated process management system, and has the characteristics of flexibility and engineering reliability, further meeting the high requirements of enterprise-level applications for process automation and intelligentization.

[0207] To achieve the above object, the embodiment of the application further provides a business process automatic processing device based on a low-code platform, please refer to Figure 4 , the device comprises:

[0208] The first determination module 41 is configured to determine a target business.

[0209] The selection module 42 is configured to select a process editing template corresponding to the target business according to the target business, wherein the process editing template is generated by the trained process modeling model, and the process editing template provides an interface of process information of a business system associated with the target business.

[0210] The second determination module 43 is configured to receive a calling instruction for the interface of the process information in the process editing template, and determine the business process information of the target business.

[0211] The execution module 44 is configured to execute the business process of the target business according to the business process information of the target business.

[0212] In some embodiments, the device further comprises:

[0213] The first monitoring module is configured to monitor the business process and record execution process information of the business process.

[0214] The selection module 42 is further configured to:

[0215] select a first process editing template corresponding to the target business according to the target business;

[0216] determine whether the first process editing template meets the execution condition according to the execution process information;

[0217] In response to the first process editing template meeting the execution condition, the first process editing template is used as the process editing template.

[0218] In some embodiments, the device further comprises:

[0219] The processing module is configured to, in response to the first process editing template not meeting the execution condition, adjust the first process editing template to a second process editing template meeting the execution condition according to the execution process information, and use the second process editing template as the process editing template.

[0220] In some embodiments, the apparatus further includes:

[0221] a second monitoring module configured to monitor the business process and record execution result information of the business process;

[0222] an input module configured to input the second process editing template as a template sample of the target business and / or the execution result information into the process modeling model for training the process modeling model.

[0223] In some embodiments, the apparatus further includes:

[0224] a third determining module configured to determine interface information of the target business according to the target business by using the interface calling model for the target business;

[0225] The second determining module 43 is further configured to:

[0226] determine an interface for the process information in the process editing template according to the interface information;

[0227] generate a calling instruction for the interface for the process information in the process editing template according to the interface for the process information;

[0228] invoke the interface and determine the business process information of the target business according to the calling instruction.

[0229] In some embodiments, the first determining module 41 is further configured to:

[0230] monitor a trigger condition for the target business, the trigger condition including at least one of a judgment condition, an exception handling condition, and an action trigger condition;

[0231] determine the target business corresponding to the trigger condition according to the trigger condition.

[0232] In some embodiments, the process modeling model includes an entity model of a business entity, a business logic model, a decision model, and an appearance model.

[0233] The selection module 42 is further configured to:

[0234] define a business entity of the target business by using the entity model of the business entity according to the target business;

[0235] define an interaction relationship of the business entity of the target business by using the business logic model in a visual connection manner according to the target business;

[0236] configure a judgment condition of a business planning engine of the target business by using the decision model according to the target business;

[0237] According to the target service, a service interaction interface of the target service is generated by using an appearance model;

[0238] According to the business entity, the interaction relationship of the business entity, the judgment condition of the business rule engine and the service interaction interface, a process editing template is constructed.

[0239] It should be pointed out that: the above description of the business process automatic processing device based on the low-code platform is similar to the description of the business process automatic processing method based on the low-code platform, and the beneficial effect of the method is not described. For the technical details not disclosed in the embodiment of the low-code platform based on the business process automatic processing device, please refer to the description of the embodiment of the low-code platform based on the business process automatic processing method.

[0240] To achieve the above object, the embodiment of the application also provides a kind of computing device, as shown in Figure 5 The computing device includes a processor 501 and a memory 502 connected to the processor 501 by a communication bus 503; wherein the memory 502 is used for automatic processing program of business process; the processor 501 is used to execute the automatic processing program of business process to realize the method of automatic processing of business process described in any of the above schemes.

[0241] Optionally, the processor 501 can be a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. Here, the program executed by the processor 501 can be stored in the memory 502 connected with the processor 501 through the communication bus 503, and the memory 502 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a ferromagnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM) used as an external cache.By way of example, and not limitation, many forms of RAM can be used, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDR SDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Sync Link Dynamic Random Access Memory (SLDRAM), Direct Rambus Random Access Memory (DRRAM). The memory 502 described herein is intended to include, without being limited to, these and any other suitable types of memory 502. The memory 502 in embodiments of the present application is for storing data of various types to support the operation of the processor 501. Examples of such data include any computer programs for the processor 501 to operate, such as an operating system and application programs, contact data, phonebook data, messages, pictures, videos, and the like. The operating system contains various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and handling hardware-based tasks.

[0242] In some embodiments, the memory 502 in the present embodiments can be a volatile memory or a nonvolatile memory, or can include both volatile and nonvolatile memory. Among them, the nonvolatile memory can be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically EPROM (EEPROM), or a flash memory. The volatile memory can be a Random Access Memory (RAM) used as an external cache. By way of example, and not limitation, many forms of RAM can be used, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous Dynamic RAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 502 of the system and method described herein is intended to include, without being limited to, these and any other suitable types of memory.

[0243] The processor 501 can be an integrated circuit chip including a processing core capable of processing signals. In implementation, each step of the above method can be completed by an integrated logic circuit or an instruction in the form of software in the processor 501. The processor 501 described above can be a general processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. Each method, step and logic block disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware code processor to execute, or be executed by a combination of hardware and software modules in the code processor. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable read only memory, a register, or other mature storage medium in the art. The storage medium is located in the storage 502, and the processor 501 reads information in the storage 502 and combines the hardware to complete the steps of the above method. In some embodiments, the embodiments described herein can be implemented by hardware, software, firmware, middleware, microcode or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), general processors, controllers, microcontrollers, microprocessors, other electronic units for executing functions described herein or a combination thereof.

[0244] For software implementation, the technology described herein can be implemented by modules (for example, procedures, functions, and so on) for performing the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0245] Another embodiment of the present application provides a computer storage medium, which stores an executable program, and the executable program, when executed by the processor 501, can implement the steps of the automatic processing method applied to the business process of the computing device. For example, one or more of the steps in the method shown in Figures 2-4

[0246] In some embodiments, the computer storage medium can include a U disk, a mobile hard disk, a read only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0247] It should be noted that the technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.

[0248] The above description is only a preferred embodiment of the present application, and is not used to limit the protection scope of the present application.​

Claims

1. A method for automatically processing business processes based on a low-code platform, characterized in that, The method includes: Define the target business; Based on the target business, a process editing template corresponding to the target business is selected. The process editing template is generated by a trained process modeling model and provides an interface for process information of business systems associated with the target business. Upon receiving a call instruction for the interface targeting the process information in the process editing template, the business process information of the target business is determined; Execute the business process of the target business based on the business process information of the target business; The process modeling model includes: an entity model of the business entity, a business logic model, a decision model, and an appearance model; the step of selecting a process editing template corresponding to the target business includes: Based on the target business, define the business entity of the target business using the entity model of the business entity; Based on the target business, the interaction relationships of the business entities of the target business are defined through a visual connection method using the business logic model; Based on the target business, the decision-making model is used to configure the judgment conditions of the business rule engine for the target business; Based on the target business, the business interaction interface of the target business is generated using the appearance model; The process editing template is constructed based on the business entity, the interaction relationship of the business entity, the judgment conditions of the business rule engine, and the business interaction interface.

2. The method according to claim 1, characterized in that, The method further includes: Monitor the business process and record the execution process information of the business process; The step of selecting a process editing template corresponding to the target business includes: Based on the target business, select the first process editing template corresponding to the target business; Based on the execution process information, determine whether the first process editing template meets the execution conditions; If the first process editing template meets the execution conditions, then the first process editing template is used as the process editing template.

3. The method according to claim 2, characterized in that, The method further includes: In response to the first process editing template not meeting the execution conditions, the first process editing template is adjusted to a second process editing template that meets the execution conditions based on the execution process information, and the second process editing template is used as the process editing template.

4. The method according to claim 3, characterized in that, The method further includes: Monitor the business process and record the execution result information of the business process; The second process editing template is used as a template sample for the target business and / or the execution result information, and is input into the process modeling model for training the process modeling model.

5. The method according to claim 1, characterized in that, The method further includes: Based on the target business, the interface information of the target business is determined using the interface call model for the target business; The step of receiving a call instruction for the interface targeting the process information in the process editing template, and determining the business process information of the target business, includes: Based on the interface information, determine the interface for the process information in the process editing template; Based on the interface of the process information, generate a calling instruction for the interface of the process information in the process editing template; According to the invocation instruction, the interface is invoked and the business process information of the target business is determined.

6. The method according to claim 1, characterized in that, The determination of the target business includes: A triggering condition for the target service is detected, and the triggering condition includes at least one of the following: a judgment condition, an exception handling condition, and an action triggering condition; Based on the triggering condition, determine the target service corresponding to the triggering condition.

7. A business process automation device based on a low-code platform, characterized in that, The device includes: The first determination module is used to determine the target business; The selection module is used to select a process editing template corresponding to the target business based on the target business. The process editing template is generated by a trained process modeling model and provides an interface for process information of business systems associated with the target business. The second determining module is used to receive a call instruction for the interface targeting the process information in the process editing template, and to determine the business process information of the target business. The execution module is used to execute the business process of the target business based on the business process information of the target business. The process modeling model includes: an entity model of the business entity, a business logic model, a decision model, and an appearance model; the step of selecting a process editing template corresponding to the target business includes: Based on the target business, define the business entity of the target business using the entity model of the business entity; Based on the target business, the interaction relationships of the business entities of the target business are defined through a visual connection method using the business logic model; Based on the target business, the decision-making model is used to configure the judgment conditions of the business rule engine for the target business; Based on the target business, the business interaction interface of the target business is generated using the appearance model; The process editing template is constructed based on the business entity, the interaction relationship of the business entity, the judgment conditions of the business rule engine, and the business interaction interface.

8. A computing device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to perform the method as described in any one of claims 1 to 6.

9. A computer storage medium, characterized in that, include: A computer storage medium stores one or more programs that can be executed by one or more processors to cause the one or more processors to perform the method as described in any one of claims 1 to 6.

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