Process task allocation method and device, storage medium and computer program product

Abstract

The invention discloses a process task allocation method and device, a storage medium and a computer program product, and relates to the technical field of task scheduling, and the method comprises the steps: obtaining business input data of a process node; calling a corresponding calculation logic according to the business input data to calculate a task characteristic value of the process node; orderly arranging the task feature values to form a multi-dimensional feature vector, and obtaining a task allocation strategy based on the multi-dimensional feature vector; and assembling a task allocation result based on the task allocation strategy, and performing flow task allocation according to the task allocation result. The feature calculation module is used for calculating various task feature values, so that the value compatibility of the task feature values is improved, the task feature value solidification is overcome, and the requirements of different business processes in different operation scenes are quickly met.

Description

Technical Field

[0001] The present application relates to the technical field of task scheduling, and in particular to a process task allocation method, device, storage medium and computer program product. Background Art

[0002] There are many business operation scenarios in the daily operation of commercial banks. The realization of various business operation scenarios usually relies on standardized business processes and a set of process engine systems running internally. Whether various business operation scenarios can be quickly realized depends on whether the process engine system can efficiently and accurately allocate process tasks. However, the process engine only supports a small number of fixed task features to allocate process tasks, and configures the task feature values ​​of different process nodes according to different business processes. Therefore, it is not compatible with the diversity of task feature values ​​of process tasks, resulting in the inability to meet the diverse task feature combination requirements for task allocation in different business scenarios, and it is difficult to adapt to the ever-expanding business scenarios.

[0003] Therefore, how to overcome the compatibility of the values ​​of task feature values ​​in process task allocation, so as to quickly meet the process task allocation needs of different business processes in different operating scenarios, has become an urgent problem to be solved in this application.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a process task allocation method, device, storage medium and computer program product, aiming to solve the technical problem of how to overcome the solidification of task characteristic values ​​and the compatibility of task characteristic values ​​in process task allocation, so as to quickly meet the process task allocation needs of different business processes in different operating scenarios.

[0006] To achieve the above objectives, the present application proposes a process task allocation method, the method comprising:

[0007] Get business input data of process nodes;

[0008] Calling corresponding calculation logic according to the business input data to calculate the task characteristic value of the process node;

[0009] Arranging the task feature values ​​in order to form a multi-dimensional feature vector, and obtaining a task allocation strategy based on the multi-dimensional feature vector;

[0010] Assemble task allocation results based on the task allocation strategy, and perform process task allocation according to the task allocation results

[0011] In one embodiment, before the step of invoking the corresponding calculation logic according to the business input data to calculate the task characteristic value of the process node, the step further includes:

[0012] Acquire historical process task allocation data and perform data enhancement on the historical process task allocation data to obtain sample process task allocation data;

[0013] Determine the sample feature value taking method according to the sample process task allocation data;

[0014] Different types of calculation logic are configured through the sample feature value taking method.

[0015] In one embodiment, the step of invoking corresponding calculation logic according to the business input data to calculate the task characteristic value of the process node includes:

[0016] Parsing the business input data to obtain a business input data parsing result;

[0017] Determine a task feature information list of the process node according to the business input data analysis result, wherein the task feature information list includes a task feature value taking method;

[0018] Based on the task feature value obtaining method, the corresponding calculation logic is called to calculate the task feature value of the process node.

[0019] In one embodiment, the step of arranging the task feature values ​​in order to form a multi-dimensional feature vector and obtaining a task allocation strategy based on the multi-dimensional feature vector includes:

[0020] Get custom sorting rules;

[0021] Arranging the task feature values ​​in order based on the custom sorting rule to form a multi-dimensional vector;

[0022] Additive quantization is performed on the multi-dimensional vector to obtain a task allocation strategy.

[0023] In one embodiment, the step of assembling the task allocation result based on the task allocation strategy and performing process task allocation according to the task allocation result includes:

[0024] Assembling a task assignment result based on the task assignment strategy, and checking whether the task assignment result has a task no handler notification configuration;

[0025] If the task assignment result has a notification configuration of "no task handler", filtering a list of processable users based on the task assignment result, and performing process task assignment according to the list of processable users;

[0026] If the task assignment result does not have a task no handler notification configuration, the process task assignment is terminated.

[0027] In one embodiment, after the step of assembling the task allocation result based on the task allocation strategy and performing process task allocation according to the task allocation result, the step further includes:

[0028] Calculate process link variables according to the task allocation result, and determine whether the process link variables hit the business rules;

[0029] The next node process task of the process node is allocated based on the judgment result of whether the process link variable hits the business rule.

[0030] In one embodiment, after the step of assembling the task allocation result based on the task allocation strategy and performing process task allocation according to the task allocation result, the step further includes:

[0031] Monitor the process task allocation, and determine the process processing efficiency based on the process task allocation;

[0032] When the process processing efficiency is lower than a preset threshold, the task allocation strategy is adjusted, and the task allocation results are reassembled according to the adjusted task allocation strategy to re-allocate process tasks.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes a process task allocation device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the process task allocation method described above.

[0034] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the process task allocation method described above are implemented.

[0035] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the process task allocation method described above are implemented.

[0036] One or more technical solutions proposed in this application have at least the following technical effects:

[0037] According to the business input data of the current process node, the corresponding feature calculation logic is called to calculate the task feature value of the current process node. There are different feature calculation logics in the feature calculation module. This modular design allows different calculation logics to be loaded according to the actual business input data to adapt to different business processes. The feature calculation module calculates the task feature value according to the business input data not only based on static rules or preset values, but can also be dynamically adjusted according to the actual input data and real-time feedback, thereby overcoming the solidification of the task feature value; the task feature values ​​are arranged in order to obtain the task allocation strategy. The task allocation strategy obtained based on the sorting of multi-dimensional task feature values ​​can be flexibly configured and adjusted according to different business needs and operation scenarios to ensure that the task can be assigned to the most appropriate processor, improve the value compatibility of the task feature value, and quickly meet the needs of different business processes in different operation scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0040] Figure 1 This is a flowchart of the first embodiment of the process engine system method of the present application;

[0041] Figure 2 This is a flow chart of the second embodiment of the process engine system method of the present application;

[0042] Figure 3 This is a flowchart of the fourth embodiment of the process engine system method of the present application;

[0043] Figure 4 This is a flowchart of the fifth embodiment of the process engine system method of the present application;

[0044] Figure 5 Provide a schematic diagram for business process handling;

[0045] Figure 6 It is a schematic diagram of the overall process of the process task allocation method;

[0046] Figure 7 A schematic diagram of the process of calculating the task characteristic value for the task allocation method of this application process;

[0047] Figure 8A flowchart for checking whether the current task assignment result has a processable person for the task assignment method of this application process.

[0048] Fig. 9 This is a schematic diagram of the module structure of the process task allocation device of the embodiment of the present application;

[0049] Fig.10 A schematic diagram of the device structure of the hardware operating environment involved in the process task allocation method in the embodiment of the present application.

[0050] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0052] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] The main solution of the embodiment of the present application is: obtain business input data from different business process nodes, dynamically select and call the corresponding feature calculation logic to calculate specific task feature values ​​according to the type and characteristics of the business input data; arrange the multiple task feature values ​​calculated in order to form a multi-dimensional feature vector, and obtain the task allocation strategy according to the multi-dimensional feature vector; assemble specific task allocation results according to the task allocation strategy, and push the task allocation results to the corresponding system components to execute the actual process task allocation.

[0054] In this embodiment, for ease of description, the following description is made by taking the identification process engine system as the execution subject.

[0055] The embodiments of the present application take into account: Since the process engine system is usually designed in the beginning, it only supports a few fixed task features to assign tasks, such as organizations, positions, and task groups, in accordance with the requirements of most business processes. With the continuous expansion of business scenarios and the rapid iteration of business systems, this mode of assigning tasks only according to a fixed combination of task features is obviously no longer able to meet the needs of banking business operations. More and more business scenarios have put forward requirements for the process engine system to support flexible configuration of task features to generate process tasks. At the same time, because the process engine system usually only supports the configuration of task feature values ​​of different process nodes according to different business processes, it is not compatible with the diversity of task feature values ​​of business processes, resulting in the inability to meet the diverse needs of task feature combinations for task assignment in different business scenarios.

[0056] Therefore, the present application provides a solution, which calls the corresponding feature calculation logic according to the business input data of the current process node to calculate the task feature value of the current process node. There are different feature calculation logics in the feature calculation module. This modular design allows different calculation logics to be loaded according to the actual business input data obtained to adapt to different business processes. The feature calculation module calculates the task feature value according to the business input data not only based on static rules or preset values, but can also be dynamically adjusted according to the actual input data and real-time feedback, thereby overcoming the solidification of the task feature value; the task feature values ​​are arranged in order to obtain the task allocation strategy, and the task allocation strategy obtained based on the sorting of multi-dimensional task feature values ​​can be flexibly configured and adjusted according to different business needs and operation scenarios to ensure that the task can be assigned to the most appropriate processor, improve the value compatibility of the task feature value, and quickly meet the needs of different business processes in different operation scenarios.

[0057] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a process engine system, etc. The following takes the process engine system as an example to illustrate this embodiment and the following embodiments.

[0058] Based on this, the embodiment of the present application provides a process engine system method, referring to Figure 1 , Figure 1 This is a flowchart of the first embodiment of the process engine system method of this application.

[0059] In this embodiment, the process task allocation method includes steps S10 to S40:

[0060] Step S10, obtaining business input data of the process node;

[0061] Business input data includes task ID, tenant ID, process instance ID, flowchart code, flowchart version, business identification code, business type, process type, task node code, task initiator, priority score, business message, task status, and task processing notes.

[0062] It should be noted that the task ID is the unique identifier of the current process task node. The tenant ID is the unique identifier of the external business system, indicating who initiated the business process. The process instance ID is the unique identifier of the current business process instance. The same business process instance usually contains multiple process task nodes. The flowchart code is the code of the flowchart used to initiate the current business process. The flowchart version indicates the specific version of the flowchart used. The business identification code is the unique identifier of a specific business and can contain multiple business process instances. The business type is the code of a certain type of business scenario (such as corporate notice deposits, structured deposits, corporate foreign exchange inward remittances, corporate foreign exchange outward remittances, etc.). The task status includes initialization, allocation exception, pending, claimed, checked out, completed, revoked, and temporarily stored. When the task status is initialization, allocation exception, and pending, the task can be reallocated.

[0063] After determining the type of business input data that needs to be collected as described above, the business input data is obtained from multiple data sources including internal databases, external system interfaces, user inputs, etc. The process engine system allows process nodes to access and obtain business input data when needed based on the API interface.

[0064] It should be noted that if the business input data comes from an external system, it is necessary to ensure real-time synchronization or regular update of the data. After obtaining the business input data of the process node, in order to ensure the smooth allocation of subsequent process tasks, the business input data needs to be verified.

[0065] Step S20, invoking corresponding calculation logic according to the business input data to calculate the task characteristic value of the process node;

[0066] The feature calculation module is the core component in the process engine system responsible for calculating the task feature value, including the feature parser and the intelligent computing core. The feature calculation module has different calculation logics. Its main function is to calculate the values ​​that can reflect the characteristics and importance of the task based on the business input data by calling specific calculation logic. These values ​​are called task feature values. For example, a task feature value may be determined by the tenant ID, flowchart code, flowchart version, and process task node code.

[0067] Parse the business input data to extract information related to the task features. Taking the text type data that may exist in the business input data as an example, the process engine system extracts words and phrases related to the task features from the text type business input data through steps such as word segmentation, part-of-speech tagging, and named entity recognition. For another example, the data structure of the structured type data in the business input data is parsed to meet the requirements of the feature calculation module.

[0068] Step S30, arranging the task feature values ​​in order to form a multi-dimensional feature vector, and obtaining a task allocation strategy based on the multi-dimensional feature vector;

[0069] The process engine system arranges all the calculated task feature values ​​in order according to certain standards or rules, such as the importance of the feature, the relevance to task allocation, or the priority in business logic. Through such arrangement, the process engine system can integrate the originally independent and scattered feature values ​​into an ordered structured data, namely a multi-dimensional feature vector.

[0070] Each dimension in the multi-dimensional feature vector represents a specific aspect of the task, such as the urgency, complexity, required resources, professional capabilities of the executor, etc. By combining the feature values ​​of these different dimensions, the process engine system can describe the characteristics of the task more comprehensively and accurately, providing a rich information basis for subsequent task allocation.

[0071] After forming the multi-dimensional feature vector, the process engine system uses the rule engine to generate a task allocation strategy. The rule engine allows users to define a series of rules and conditions based on business needs. When the multi-dimensional feature vector meets these rules and conditions, the process engine system will automatically perform the corresponding task allocation operation.

[0072] When faced with multi-dimensional feature vectors for complex task assignments, the process engine system uses a variety of machine learning algorithms to generate task assignment strategies. For example, the decision tree algorithm can simulate the human decision-making process by building a decision tree model, thereby making the best task assignment decision based on the different values ​​of the multi-dimensional feature vector. The random forest algorithm can improve the accuracy and stability of task assignment by building multiple decision trees and combining their prediction results. The neural network algorithm can simulate the working mode of human brain neurons and learn complex task assignment rules through a large amount of training data.

[0073] Step S40, assembling task allocation results based on the task allocation strategy, and performing process task allocation according to the task allocation results.

[0074] The process engine system first determines the specific allocation details of each task according to the instructions in the task allocation strategy. The specific allocation details include but are not limited to: the allocation object, which is used to determine which executor or executors (such as employees, departments, machines, etc.) will be assigned to a specific task; the allocation time, which is used to set the specific time point or time period for the task to start execution; the expected completion time, which is used to estimate the completion time of the task based on the complexity of the task and the ability of the allocation object; the priority, if multiple tasks need to be assigned at the same time, the priority needs to be set according to the importance and urgency of the task.

[0075] The process engine system integrates the above allocation details into one or more task allocation records, which exist in the form of database entries, JSON objects, XML documents, etc., and contain all necessary task and executor information.

[0076] The process engine system notifies the corresponding executors or system components of the task allocation results based on the preset or dynamically selected communication mechanism. The preset or dynamically selected communication mechanism may include: message queues, API calls.

[0077] This embodiment provides a process task allocation method, which calls the corresponding feature calculation logic according to the business input data of the current process node to calculate the task feature value of the current process node. There are different feature calculation logics in the feature calculation module. This modular design allows different calculation logics to be loaded according to the actual business input data to adapt to different business processes. The feature calculation module calculates the task feature value according to the business input data not only based on static rules or preset values, but can be dynamically adjusted according to the actual input data and real-time feedback, thereby overcoming the solidification of the task feature value; the task feature values ​​are arranged in order to obtain the task allocation strategy. The task allocation strategy obtained based on the sorting of multi-dimensional task feature values ​​can be flexibly configured and adjusted according to different business needs and operation scenarios to ensure that the task can be assigned to the most appropriate processor, improve the value compatibility of the task feature value, and quickly meet the needs of different business processes in different operation scenarios.

[0078] In a feasible implementation, step S30 may include steps S31 to S33:

[0079] Step S31, obtaining a custom sorting rule;

[0080] Custom sorting rules can be used to define the sorting criteria for task feature values. Users can customize sorting rules based on multiple factors such as task priority, urgency, resource requirements, skill requirements, execution time, cost budget, etc. Custom sorting rules can be single-dimensional or a combination of multiple dimensions, depending on the user's needs and goals.

[0081] Step S32, arranging the task feature values ​​in order based on the custom sorting rule to form a multi-dimensional vector;

[0082] Sort the characteristic values ​​of each task (such as priority value, urgency level, required resources, skill requirement tags, etc.) according to the custom sorting rules. Since task characteristics are usually multi-dimensional, the sorted result will form a multi-dimensional vector. Each dimension in this vector represents a specific task feature, and the elements of the vector are arranged in order according to the sorting rules.

[0083] Step S33, performing additive quantization on the multi-dimensional vector to obtain a task allocation strategy.

[0084] Additive quantization is a series of processing such as weighted summation, weighted average, and fuzzy comprehensive evaluation of each element in the multidimensional vector (i.e., task characteristic values), which converts the multidimensional vector into a single value or evaluation level, which is then used to guide task allocation decisions and form task allocation decisions.

[0085] In a feasible implementation, step S40 may include steps S41 to S43:

[0086] Step S41, assembling a task assignment result based on the task assignment strategy, and checking whether the task assignment result has a task no handler notification configuration;

[0087] The process engine system assembles detailed information such as tasks, assigned objects, assigned time, expected completion time, etc. into specific task assignment results according to the instructions in the task assignment strategy, and stores the task assignment results in a structured form for subsequent processing and query.

[0088] After assembling the task assignment results, the process engine system will check whether the task assignment results contain the "Task No Handler Notification Configuration". The Task No Handler Notification Configuration is usually used to specify the notification strategy or subsequent actions that the process engine system should take when it cannot directly find a suitable handler. For example, when all preset assignment objects cannot handle the task, the system may need to send a notification to a specific administrator or team.

[0089] Step S42, if the task assignment result has a task no handler notification configuration, filtering a list of processable users based on the task assignment result, and performing process task assignment according to the list of processable users;

[0090] If the task assignment result includes a notification configuration for a task with no handler, the process engine system further filters out a list of users who can process the task, which includes executors, backup executors, other employees with similar skills or experience, etc.

[0091] After filtering out the list of processable users, the process engine system will select one or more executors from the list according to a certain priority or rule (such as polling, load balancing, etc.) and assign tasks. The assignment process may involve operations such as updating the task status and sending notification messages to the executors.

[0092] If the filtered user list is empty, although there is a task no handler notification configuration, because the process engine system finds that there is no suitable user to handle the current task, it notifies the relevant personnel or system components in a visual way. The visual notification may display a warning or error message through the user interface (such as the dashboard of the workflow management system, the task list, etc.), clearly informing that there is no handler for the current task node. The visual notification method helps to find problems in time and prompt relevant personnel to take necessary actions (such as re-evaluating the task allocation strategy, adding new handlers, etc.).

[0093] Step S43, based on the task feature value obtaining method, the corresponding calculation logic in the intelligent computing core is called to calculate the task feature value of the process node.

[0094] If the task assignment result does not include the task no handler notification configuration, and the process engine system cannot find a suitable executor based on the current task assignment strategy, the process engine system will choose to end the process task assignment process and mark the task as pending or assignment failed.

[0095] In this embodiment, by introducing the task no handler notification configuration and the available user list screening mechanism, it is possible to more flexibly deal with various situations in the task allocation process. This can not only improve the accuracy and efficiency of task allocation, but also reduce task delays or failures caused by the inability to find suitable executors.

[0096] Based on the first embodiment of the present application, the second embodiment of the present application is proposed. In the second embodiment of the present application, the same or similar contents as those of the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following.

[0097] On this basis, please refer to Figure 2 Before step S20, the process task allocation method further includes steps S121 to S123:

[0098] Step S121, acquiring historical process task allocation data and performing data enhancement on the historical process task allocation data to obtain sample process task allocation data;

[0099] Collect process task allocation data over historical time. The process task allocation data includes various attributes of the task (such as type, complexity, required skills, etc.), information of the executor (such as department, position, experience, etc.), as well as allocation results and subsequent performance indicators (such as completion time, quality score, etc.).

[0100] In order to increase the generalization and robustness of the model, data enhancement is performed on the process task allocation data. In the context of task allocation data, data enhancement may be more about simulating task allocation situations in different scenarios, or simulating different task complexities by adjusting the range of attribute values.

[0101] Step S122, determining a sample feature value taking method according to the sample process task allocation data;

[0102] The feature calculation module consists of two main parts: the feature parser and the intelligent computing core. The design goal of the feature parser is to extract key features that have an important impact on task allocation decisions from complex task allocation data, and determine the appropriate sample feature value method based on different features. This requires the parser to be able to analyze the correlation between different features and the contribution of different features to the task allocation results.

[0103] The feature parser uses domain knowledge to identify key features, or discovers potential associations in sample process task allocation data through data exploration (such as data visualization, statistical testing, etc.), thereby extracting features that may have an impact on task allocation decisions from sample process task allocation data. In the feature selection process, care should be taken to avoid selecting too many irrelevant or redundant features to reduce computational complexity and improve the interpretability of the model. After completing feature selection, determine the appropriate sample feature value method based on the selected key features.

[0104] It should be noted that the implementation of the feature contribution calculation logic is mainly based on the regression model framework, and the features extracted from the sample process allocation data are used to train the regression model framework, and the relevant parameters of the regression model framework are continuously adjusted so that the regression model can extract task features from the business input data.

[0105] Step S123, configuring different types of calculation logic according to the sample feature value taking method.

[0106] Different types of computing logic are configured in the intelligent computing core according to the sample feature value selection method. Since the sample process task allocation data contains data of multiple data types, the computing logic needs to be configured according to the data of different data types and different feature value selection methods.

[0107] Among them, the natural language processing model is used to configure the data allocation and sample feature value selection method for text-type tasks. The intelligent computing core is a metaphor or refers to a broader intelligent processing framework, which includes not only the natural language processing model, but also the fully connected neural network model framework and the random forest model framework for processing different types of data.

[0108] For text-based task assignment data, design or select a suitable natural language processing model to understand text information such as task descriptions and executor feedback. For numerical and categorical data, design a fully connected neural network model to use the numerical features of these data to make task assignment decisions. Given the excellent performance of random forests in handling classification and regression problems, it can be used as another model framework to comprehensively evaluate the matching degree between tasks and executors. Integrate the above different types of models to form a comprehensive intelligent computing core. Improve the accuracy and robustness of the overall prediction through voting mechanisms, stacking or weighted averaging.

[0109] In this embodiment, by performing data enhancement on historical process task allocation data, generating more diverse sample data, and designing a feature parser with feature contribution calculation logic, the importance of each feature in the task allocation decision can be dynamically evaluated. This mechanism enables the system to recognize and adapt to changes in feature values ​​in different scenarios, avoiding over-reliance on certain fixed feature values. During the design process of the feature parser and the intelligent computing core, in-depth feature engineering will be carried out, including steps such as feature selection, feature construction, and feature conversion, aiming to extract the most valuable features for task allocation decisions and ensure that these features have good value compatibility in different business processes and operational scenarios. The different calculation logics in the feature calculation module improve the flexibility and scalability of the process engine system, effectively overcome the problems of task feature value solidification and value compatibility, thereby quickly meeting the process task allocation needs of different business processes in different operational scenarios.

[0110] Based on the first embodiment and / or the second embodiment of the present application, the third embodiment of the present application is proposed. In the third embodiment of the present application, the same or similar contents as those of the first embodiment and / or the second embodiment can be referred to the above introduction, and will not be repeated in the following.

[0111] In this embodiment, the step S20 of invoking the corresponding feature calculation module according to the business input data to calculate the task feature value of the process node may include steps S21 to S23:

[0112] Step S21, parsing the business input data to obtain a business input data parsing result;

[0113] The process engine system receives business input data from users, which may include detailed descriptions of tasks, information about executors, time requirements, resource requirements, and other information. The feature parser is trained using sample process task allocation data, which contains business input data. The feature parser is designed to process these diverse input data and extract key information that is useful for task allocation decisions. The feature parser contains multiple submodules, each of which is responsible for processing different types of input data (such as text, numerical values, categorical data, etc.) and applying corresponding parsing rules to extract features.

[0114] Step S22, determining a task feature information list of the process node according to the business input data analysis result, wherein the task feature information list includes a task feature value taking method;

[0115] The task feature value acquisition method is the method by which the task feature of the process task node participating in the task allocation calculation obtains specific values. The task feature value acquisition methods include directly using the feature value configured by the task feature, using the value of a field in the business input data, using the business element value mapped to a field in the business input data, using the business element value mapped to multiple fields in the business input data, and obtaining through other business system interfaces.

[0116] It should be noted that the fixed value of task characteristics is to directly configure the constant value of task characteristics. For example, if a task node can only be processed by a fixed position, the fixed value of the task characteristics can be directly assigned to a position code value. The task characteristic value selection method supports configurability, which can well support the diverse requirements of task characteristic values ​​in different business scenarios.

[0117] After the feature parser parses the business input data, the process engine system generates a task feature information list based on the data parsing results. This list lists in detail all the task features related to the current process node, as well as the value-taking method for each feature. The value-taking method may include direct value-taking (such as a value directly extracted from the input data), calculated value-taking (such as a value that needs to be calculated through an algorithm or model), conditional value-taking (such as selecting different values ​​based on specific conditions), etc. The generation of the task feature information list is the basis for the subsequent calculation of the task feature value.

[0118] Step S23, based on the task feature value obtaining method, the corresponding calculation logic is called to calculate the task feature value of the process node.

[0119] According to the value selection method in the task feature information list, the corresponding calculation logic in the intelligent computing core is called to calculate the value of each task feature. The intelligent computing core is a framework that integrates multiple computing models and algorithms and can handle different types of computing tasks. For features that need to be directly valued, the corresponding values ​​are directly extracted from the input data; for features that need to be calculated, the corresponding algorithm or model is called for calculation; for features with conditional values, the appropriate value is selected according to the preset conditional logic.

[0120] Taking the data in the task feature information list where the data type is text type and the value method is field value as an example, the intelligent computing core calls the natural language processing model to process the data and calculates the task feature value based on the processing results.

[0121] The task feature information list is traversed to check whether all the task feature values ​​listed in the list have been calculated. The internal state or counter of the process engine system records the number of features that have been calculated and compares it with the total number of features in the list.

[0122] If the process engine system finds that there are uncalculated task feature values, it will call the corresponding feature calculation module to calculate according to the value selection method specified in the task feature information list. This calculation module may be based on natural language processing, machine learning, rule engine, or any other algorithm or model suitable for processing this type of feature value. After the calculation is completed, the process engine system will store the results in an appropriate location for subsequent use or aggregation.

[0123] Once all task feature values ​​are calculated, the process engine system will perform a summary operation to collect all calculated feature values ​​into a data structure (such as a dictionary, list, or object) so that the subsequent task allocation decision process can easily access and use these values. The summary operation may also include some additional processing, such as data cleaning, format conversion, or standardization to ensure the consistency and comparability of feature values.

[0124] In this embodiment, the feature parser extracts key information useful for task allocation decisions from complex and diverse input data, and flexibly adjusts the parsing strategy according to different input data, thereby avoiding dependence on a specific format or structure. This flexibility helps to overcome the problem of solidification of task feature values, and is no longer limited to processing input data of fixed format or type. The task feature information list not only includes the task features themselves, but also clarifies the value-taking method of each feature. This design enables the process engine system to flexibly define and modify task features and their value-taking methods according to different business processes and operation scenarios. The intelligent computing core is the core part of executing actual computing tasks, which includes a variety of computing models and algorithms and can handle different types of computing tasks. By improving the flexibility of task feature values, enhancing the adaptability of task feature information, providing diversified computing logic, and realizing the ability to quickly respond to different needs, the problem of task feature value solidification and task feature value compatibility in process task allocation is effectively overcome, thereby meeting the process task allocation needs of different business processes under different operation scenarios that can quickly adapt to different business processes.

[0125] Based on the above-mentioned embodiments of the present application, a fourth embodiment of the present application is proposed. In the fourth embodiment of the present application, the same or similar contents as those of the above-mentioned embodiments can be referred to the above introduction and will not be repeated later.

[0126] On this basis, please refer to Figure 3 , Figure 3 A flowchart of the fourth embodiment of the task allocation method provided for the present application process.

[0127] In this embodiment, after step S40 of assembling the task allocation result based on the task allocation strategy and allocating the process tasks according to the task allocation result, steps S50 to S60 are also included:

[0128] Step S50, calculating process link variables according to the task allocation result, and determining whether the process link variables match the business rules;

[0129] Calculate process variables based on the task assignment results. These variables may represent the status, performance, cost, or any other business-related indicators of a link in the process. After the calculation is completed, the system will match these variables with predefined business rules to determine whether any rules are hit. Business rules are usually determined by the company's business logic, policies, regulations, or industry standards, and are used to guide process execution and decision-making.

[0130] Step S60, assigning the next node process task of the process node based on the judgment result of whether the process link variable hits the business rule.

[0131] If a process link variable hits a business rule, the system may trigger a specific task or action based on the conditions or logic specified by the rule. For example, if the cost of a process link exceeds the budget threshold, the system may automatically assign the task to the cost control department for review and adjustment. If a process link variable does not hit any business rule, the system may continue to execute the process according to the default logic or path.

[0132] In this embodiment, by calculating the process link variables and determining whether the process link hits the business rules, the system is allowed to dynamically adjust the execution path of the process according to real-time data and business rules, thereby improving the flexibility and response speed of the process. In addition, by embedding business rules into the process task allocation process, the system can ensure that the execution of the process always meets the business needs and compliance requirements of the enterprise.

[0133] Based on the above-mentioned embodiments of the present application, a fifth embodiment of the present application is proposed. In the fifth embodiment of the present application, the same or similar contents as those of the above-mentioned embodiments can be referred to the above introduction and will not be repeated later.

[0134] On this basis, please refer to Figure 4 , Figure 4 A flowchart of the fifth embodiment of the task allocation method provided for the present application process.

[0135] In this embodiment, after step S40 of assembling the task allocation result based on the task allocation strategy and performing process task allocation according to the task allocation result, steps A50 to A60 are also included:

[0136] Step A50, monitoring the process task allocation, and determining the process processing efficiency based on the process task allocation;

[0137] Monitor the execution of process task assignments in real time, including key indicators such as task processing time, task completion rate, and task processor efficiency. Further determine process processing efficiency based on the above key indicators.

[0138] Step A60: when the process processing efficiency is lower than a preset threshold, the task allocation strategy is adjusted, and the task allocation results are reassembled according to the adjusted task allocation strategy to re-allocate process tasks.

[0139] Dynamically adjust the task allocation strategy based on monitoring results. When it is detected that the processing efficiency of a task is lower than the preset threshold, the task is automatically reallocated to other processors, or the priority setting in the task allocation strategy is adjusted to optimize the overall task processing efficiency. And the process tasks are reallocated according to the adjusted task allocation strategy.

[0140] In this embodiment, the process task allocation is monitored. When the process processing efficiency is lower than a preset threshold, the task allocation strategy is adjusted, and the task allocation results are reassembled according to the adjusted task allocation strategy to re-allocate the process tasks, so that the process engine system can quickly identify and solve the bottleneck problems in task allocation, ensuring that tasks are efficiently and reasonably allocated.

[0141] The following combination Figure 5 , Figure 6 , Figure 7 as well as Figure 8 The overall process of the task allocation method of this application process is explained in detail, including: Figure 5 Provide a schematic diagram for business process handling; Figure 6 It is a schematic diagram of the overall process of the process task allocation method; Figure 7 A schematic diagram of the process of calculating the task characteristic value for the task allocation method of this application process; Figure 8 A flowchart for checking whether the current task assignment result has a processable person for the task assignment method of this application process.

[0142] like Figure 5 As shown, in the business process of commercial banks, the process engine system usually serves as a basic platform, providing functions such as process initiation, process node driving, process task generation, process task acquisition, and process task submission. The main content of this application is in the process task generation link, that is, Figure 5 The process task check-out and process task check-in are shown.

[0143] like Figure 6 As shown, a process task allocation method supporting multiple operation scenarios includes the following steps:

[0144] S1: Get the business input data of the current process node and parse it;

[0145] Business input data includes task ID, tenant ID, process instance ID, flowchart code, flowchart version, business identification code, business type, process type, task node code, task initiator, priority score, business message, task status, and task processing notes.

[0146] S2: Obtain the task feature information of the current node according to the tenant ID, business type, flowchart code, flowchart version and node code of the current process node;

[0147] Task feature information includes feature code, feature value method, feature fixed value, and feature value path. Task features are business element fields that process task nodes rely on for task allocation, such as organization, position, user group, product group, etc. A task feature is determined by the tenant ID, flowchart code, flowchart version, and process task node code.

[0148] S3: Calculate all task feature values ​​of the current process node according to the task feature value selection method;

[0149] The task feature value acquisition method is the method by which the task feature of the process task node participating in the task allocation calculation obtains specific values. The task feature value acquisition methods include directly using the feature value configured by the task feature, using the value of a field in the business input data, using the business element value mapped to a field in the business input data, using the business element value mapped to multiple fields in the business input data, and obtaining through other business system interfaces.

[0150] like Figure 7 As shown, step S3 specifically includes: S301: traverse the task feature information list of the current process node; S302: check whether all task feature values ​​have been calculated; if so, execute step S304; if not, execute step S303; S303: according to the feature value taking method, call the corresponding feature calculation module to calculate the task feature value; after the calculation is completed, set i=i+1, and return to step S301; S304: summarize all task feature values ​​of the current process node.

[0151] S4: Obtain the task allocation strategy of the current process node, assemble the task allocation results according to the task allocation strategy and save them;

[0152] The task allocation strategy is an ordered arrangement of one or more task features, which determines the order in which the task features are spliced ​​together in the task allocation result. For example, a task node needs to be assigned to a person in a certain position under a certain organization to handle it. The organization is represented by organ and the position is represented by role. Then the task allocation strategy can be simply described as [organ-role]. A task allocation strategy is determined by the tenant ID, flowchart code, flowchart version, and process task node code.

[0153] The task assignment result is a string of task feature values ​​concatenated in the order specified by the task assignment strategy, i.e., the task participant. If a user wants to obtain a process task, he must configure it with the same task feature as the task node. The system generates user participants based on the task features owned by the user according to the task assignment strategy. When a user obtains a task through the system, the user participant is compared with the task participant. If the user participant is equal to the task participant, it means that the user can handle this task.

[0154] S5: Check whether there is anyone who can handle the current task assignment result. If not, notify the business scenario party.

[0155] like Figure 8As shown, step S5 specifically includes: S501: whether there is a task with no handler notification configuration; if yes, execute step S502, if not, end the assignment of the current process task; S502: obtain the task participants of the current task node according to the task ID (i.e., the task assignment result); S503: filter out the list of processable users according to the task participants. S504: whether the processable user list is empty; if yes, execute step S505; if not, end the assignment of the current process task; S505: notify the business scenario party that there is no handler for the current task node.

[0156] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the task allocation method of the process of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0157] This application also provides a process task allocation device, please refer to Fig. 9 , the process task allocation device comprises:

[0158] A business input data acquisition module 10 is used to acquire business input data of a process node;

[0159] Business input data includes task ID, tenant ID, process instance ID, flowchart code, flowchart version, business identification code, business type, process type, task node code, task initiator, priority score, business message, task status, and task processing notes.

[0160] A feature calculation module 20, used to call corresponding calculation logic to calculate the task feature value of the process node according to the business input data;

[0161] The feature calculation module is the core component in the process engine system responsible for calculating the task feature value, including the feature parser and the intelligent computing core. The main function of the feature calculation module is to calculate the values ​​that can reflect the characteristics and importance of the task based on the business input data through specific algorithms and models. These values ​​are called task feature values. For example, a task feature value may be determined by the tenant ID, flowchart code, flowchart version, and process task node code.

[0162] A task allocation strategy module 30, configured to arrange the task feature values ​​in order to form a multi-dimensional feature vector, and obtain a task allocation strategy based on the multi-dimensional feature vector;

[0163] The process engine system arranges all the calculated task feature values ​​in order according to certain standards or rules, such as the importance of the feature, the relevance to task allocation, or the priority in business logic. Through such arrangement, the process engine system can integrate the originally independent and scattered feature values ​​into an ordered structured data, namely a multi-dimensional feature vector.

[0164] The task allocation result module 40 is used to assemble the task allocation result based on the task allocation strategy and perform process task allocation according to the task allocation result.

[0165] The process task allocation device provided by the present application adopts the process task allocation method in the above embodiment, which can solve the technical problem of process task allocation. Compared with the prior art, the beneficial effects of the process task allocation device provided by the present application are the same as the beneficial effects of the process task allocation method provided by the above embodiment, and other technical features in the process task allocation device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0166] The present application provides a process task allocation device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the process task allocation method in the above-mentioned embodiment one.

[0167] Reference below Fig.10 , which shows a schematic diagram of the structure of a process task allocation device suitable for implementing the embodiment of the present application. The process task allocation device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Fig.10 The process task allocation device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0168] like Fig.10As shown, the process task allocation device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the process task allocation device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the process task distribution device to communicate wirelessly or wired with other devices to exchange data. Although the process task distribution device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0169] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0170] The process task allocation device provided by the present application adopts the process task allocation method in the above embodiment, which can solve the technical problem of process task allocation. Compared with the prior art, the beneficial effects of the process task allocation device provided by the present application are the same as the beneficial effects of the process task allocation method provided by the above embodiment, and the other technical features in the process task allocation device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0171] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0172] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0173] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the process task allocation method in the above-mentioned embodiment.

[0174] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0175] The computer-readable storage medium may be included in the process task allocation device; or may exist independently without being assembled into the process task allocation device.

[0176] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the process task allocation device, the process task allocation device enables the process task allocation device to: obtain business input data of the process node; call the corresponding calculation logic according to the business input data to calculate the task feature value of the process node; arrange the task feature values ​​in order to form a multi-dimensional feature vector, and obtain a task allocation strategy based on the multi-dimensional feature vector; assemble the task allocation results based on the task allocation strategy, and perform process task allocation according to the task allocation results.

[0177] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0178] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0179] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0180] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned process task allocation method, and can solve the technical problem of process task allocation. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the process task allocation method provided by the above-mentioned embodiment, and will not be repeated here.

[0181] The present application also provides a computer program product, including a computer program, which implements the steps of the process task allocation method as described above when executed by a processor.

[0182] The computer program product provided by this application can solve the technical problem of process task allocation. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the process task allocation method provided by the above embodiment, which will not be repeated here.

[0183] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A process task allocation method, characterized in that: The method comprises: Get business input data of process nodes; Calling corresponding calculation logic according to the business input data to calculate the task characteristic value of the process node; Arranging the task feature values ​​in order to form a multi-dimensional feature vector, and obtaining a task allocation strategy based on the multi-dimensional feature vector; Assemble task allocation results based on the task allocation strategy, and perform process task allocation according to the task allocation results.

2. The method according to claim 1, characterized in that Before the step of invoking the corresponding calculation logic according to the business input data to calculate the task characteristic value of the process node, the following step is further included: Acquire historical process task allocation data and perform data enhancement on the historical process task allocation data to obtain sample process task allocation data; Determine the sample feature value taking method according to the sample process task allocation data; Different types of calculation logic are configured through the sample feature value taking method.

3. The method according to claim 2, characterized in that The step of invoking the corresponding calculation logic according to the business input data to calculate the task characteristic value of the process node comprises: Parsing the business input data to obtain a business input data parsing result; Determine a task feature information list of the process node according to the business input data analysis result, wherein the task feature information list includes a task feature value taking method; Based on the task feature value obtaining method, the corresponding calculation logic is called to calculate the task feature value of the process node.

4. The method according to claim 1, characterized in that The step of arranging the task feature values ​​in order to form a multi-dimensional feature vector and obtaining a task allocation strategy based on the multi-dimensional feature vector includes: Get custom sorting rules; Arranging the task feature values ​​in order based on the custom sorting rule to form a multi-dimensional vector; Additive quantization is performed on the multi-dimensional vector to obtain a task allocation strategy.

5. The method according to claim 1, characterized in that The step of assembling the task allocation result based on the task allocation strategy and performing process task allocation according to the task allocation result comprises: Assembling a task assignment result based on the task assignment strategy, and checking whether the task assignment result has a task no handler notification configuration; If the task assignment result has a notification configuration of "no task handler", filtering a list of processable users based on the task assignment result, and performing process task assignment according to the list of processable users; If the task assignment result does not have a task no handler notification configuration, the process task assignment is terminated.

6. The method according to claim 1, characterized in that After the step of assembling the task allocation result based on the task allocation strategy and performing process task allocation according to the task allocation result, the following step is further included: Calculate process link variables according to the task allocation result, and determine whether the process link variables hit the business rules; The next node process task of the process node is allocated based on the judgment result of whether the process link variable hits the business rule.

7. The method according to claim 1, characterized in that After the step of assembling the task allocation result based on the task allocation strategy and performing process task allocation according to the task allocation result, the following step is further included: Monitor the process task allocation, and determine the process processing efficiency based on the process task allocation; When the process processing efficiency is lower than a preset threshold, the task allocation strategy is adjusted, and the task allocation results are reassembled according to the adjusted task allocation strategy to re-allocate process tasks.

8. A process task allocation device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the process task allocation method according to any one of claims 1 to 7.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the process task allocation method according to any one of claims 1 to 7 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the process task allocation method according to any one of claims 1 to 7 are implemented.

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