Request Processing Method, Device, and Electronic Device for Process Modeling

Abstract

The present disclosure provides a request processing method for process modeling, which can be applied to the field of artificial intelligence technology. The request processing method for process modeling includes: receiving modeling task requests submitted by M users, where the modeling task requests include modeling data and M≥2; when it is determined that there is the same modeling data in the modeling task requests submitted by the M users, recording the same modeling data to obtain intersection data; determining target users from the M users based on the intersection data according to a preset rule; and processing the modeling task requests submitted by the target users. The present disclosure also provides a request processing device, equipment, and storage medium for process modeling.

Description

Technical Field

[0001] The present disclosure relates to the field of artificial intelligence, and more particularly to a request processing method, apparatus, device, medium and program product for process modeling. Background Art

[0002] Process modeling refers to standardizing and organizing the same or similar processes, extracting customers, products, and channels as variable factors, and using standardized language to structurally and normatively describe business processes. Current process modeling systems contain a large number of business models. For example, a third-level activity may correspond to multiple fourth-level tasks, and a fourth-level task may correspond to multiple fifth-level steps. Other third-level activities can correspond to the same fourth-level tasks and the same fifth-level steps, thus forming a tree-structured system. When performing process modeling, when there are the same business models in the modeling tasks submitted by multiple users, the modeling system does not allow the submission of modeling tasks and only allows submission when there is no business model conflict.

[0003] In the process of implementing the inventive concept of the present disclosure, the inventors found that there are at least the following problems in the related art: Since the process modeling system includes a large number of business models, the probability of the same business model existing between different modeling tasks is relatively high. In the case where there are the same business models in the modeling tasks submitted by multiple users, the related art cannot execute the modeling tasks, resulting in poor user experience and low modeling efficiency. Summary of the Invention

[0004] In view of the above problems, the present disclosure provides a request processing method, apparatus, device, medium and program product for process modeling.

[0005] According to a first aspect of the present disclosure, there is provided a request processing method for process modeling, including:

[0006] Receiving modeling task requests submitted by M users, where the modeling task requests include modeling data, and M≥2;

[0007] When it is determined that there is the same modeling data in the modeling task requests submitted by the M users, recording the same modeling data to obtain intersection data;

[0008] Determining target users from the M users based on the intersection data according to a preset rule; and

[0009] Processing the modeling task requests submitted by the target users.

[0010] According to an embodiment of the present disclosure, determining target users from the M users based on the intersection data according to a preset rule includes:

[0011] For each of the above M users, determine the occupancy value corresponding to the user according to the above intersection data, and obtain M such occupancy values;

[0012] Determine the maximum occupancy value among the M occupancy values to obtain the target occupancy value;

[0013] Determine that the user corresponding to the above target occupancy value is the above target user.

[0014] According to an embodiment of the present disclosure, the above intersection data includes a service model and a category label of the service model;

[0015] The above determining the occupancy value corresponding to the user according to the above intersection data includes:

[0016] Determine the service model corresponding to the i-th user according to the above intersection data to obtain the i-th intersection model set, where 1 ≤ i ≤ M;

[0017] Determine the i-th model category set corresponding to the i-th user according to the above i-th intersection model set and the above category label, where the i-th model category set includes the category labels of the service models in the above i-th intersection model set;

[0018] Determine the users among the above M users who have an intersection with the i-th user to obtain the i-th intersection user set, where the users who have an intersection with the i-th user include the service models in the above i-th intersection model set in the modeling task requests submitted by the users;

[0019] Determine the above occupancy value corresponding to the i-th user according to the above i-th intersection model set, the above i-th model category set, and the above i-th intersection user set.

[0020] According to an embodiment of the present disclosure, the above request processing method for process modeling further includes:

[0021] Remove duplicates from the duplicate service models in the above i-th intersection model set to obtain the deduplicated i-th intersection model set;

[0022] Remove duplicates from the duplicate category labels in the above i-th model category set to obtain the deduplicated i-th model category set;

[0023] The above determining the above occupancy value corresponding to the i-th user according to the above i-th intersection model set, the above i-th model category set, and the above i-th intersection user set includes:

[0024] Determine the above occupancy value corresponding to the i-th user according to the above i-th intersection model set, the deduplicated i-th intersection model set, the above i-th model category set, the deduplicated i-th model category set, and the above i-th intersection user set.

[0025] According to an embodiment of the present disclosure, determining the occupancy value corresponding to the i-th user based on the above-mentioned i-th intersection model set, the deduplicated i-th intersection model set, the above-mentioned i-th model category set, the deduplicated i-th model category set, and the above-mentioned i-th intersection user set includes:

[0026] Determining the number of i-th intersection users corresponding to the i-th user according to the above-mentioned i-th intersection user set;

[0027] Determining the ratio of the number of the i-th intersection users to the number of the M users to obtain a first occupancy value;

[0028] Determining the number of i-th intersection models corresponding to the i-th user according to the above-mentioned i-th intersection model set;

[0029] Determining the ratio of the number of the i-th intersection models to the number of the deduplicated i-th intersection models to obtain a second occupancy value;

[0030] Determining the number of i-th model categories corresponding to the i-th user according to the above-mentioned i-th model category set;

[0031] Determining a third occupancy value based on the number of the i-th model categories and the number of the deduplicated i-th model categories;

[0032] Determining the occupancy value corresponding to the i-th user according to the above-mentioned first occupancy value, the above-mentioned second occupancy value, and the above-mentioned third occupancy value.

[0033] According to an embodiment of the present disclosure, the above-mentioned category labels include one or more of value chain, business domain, secondary process, tertiary activity, quaternary task, quinary step, and business component.

[0034] A second aspect of the present disclosure provides a request processing apparatus for process modeling, including:

[0035] A receiving module, configured to receive modeling task requests submitted by M users, where the above-mentioned modeling task requests include modeling data, and M≥2;

[0036] A recording module, configured to record the above-mentioned identical modeling data to obtain intersection data when it is determined that there is identical modeling data in the modeling task requests submitted by the above-mentioned M users;

[0037] A determining module, configured to determine target users from the above-mentioned M users based on the above-mentioned intersection data according to a preset rule; and

[0038] A processing module, configured to process the modeling task requests submitted by the above-mentioned target users.

[0039] A third aspect of the present disclosure provides an electronic device, including: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to execute the above-mentioned request processing method for process modeling.

[0040] A fourth aspect of the present disclosure further provides a computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor is caused to execute the above-mentioned request processing method for process modeling.

[0041] A fifth aspect of the present disclosure further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the above-mentioned request processing method for process modeling is implemented.

[0042] According to an embodiment of the present disclosure, by receiving modeling task requests submitted by M users, it is determined whether there is the same modeling data according to the modeling data in the modeling task requests. When it is determined that there is the same modeling data in the modeling task requests submitted by M users, the same modeling data is recorded to obtain intersection data; target users are determined from M users based on preset rules according to the intersection data; the modeling task requests submitted by the target users are processed. By optimizing the modeling method, it is supported that when there is the same modeling data in the modeling data submitted by multiple users, the modeling data can be partially submitted, so that the modeling task can be smoothly executed, improving the user experience and modeling efficiency. At least partially solve the technical problem that when multiple submitted modeling tasks have the same modeling data, the modeling tasks cannot be executed, thus affecting the user experience and modeling efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Through the following description of the embodiments of the present disclosure with reference to the drawings, the above-mentioned content and other objects, features and advantages of the present disclosure will become clearer. In the drawings:

[0044] Figure 1 Schematically shows an application scenario diagram of a request processing method, device, device, medium and program product for process modeling according to an embodiment of the present disclosure;

[0045] Figure 2 Schematically shows a flowchart of a request processing method for process modeling according to an embodiment of the present disclosure;

[0046] Figure 3 Schematically shows a flowchart of a method for determining a target user according to an embodiment of the present disclosure;

[0047] Figure 4 Schematically shows a flowchart of a request processing method for process modeling according to another embodiment of the present disclosure;

[0048] Figure 5 Schematically shows a structural block diagram of a request processing device for process modeling according to an embodiment of the present disclosure;

[0049] Figure 6 Schematically shows a structural block diagram of a determination module according to an embodiment of the present disclosure; and

[0050] Figure 7 Schematically shows a block diagram of an electronic device suitable for implementing a request processing method for process modeling according to an embodiment of the present disclosure. Detailed implementation manners

[0051] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the following detailed description, for the sake of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is obvious that one or more embodiments can also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present disclosure.

[0052] The terms used herein are merely for describing specific embodiments and are not intended to limit the present disclosure. The terms "including", "comprising", etc. used herein indicate the presence of the described features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0053] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0054] In the case of using expressions such as "at least one of A, B, and C", generally, it should be interpreted according to the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include, but is not limited to, a system having only A, only B, only C, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0055] Explanation of related terms:

[0056] Process model: A standardized and structured model formed by presenting, summarizing, and generalizing the business execution processes triggered by external events or initiated internally. The process model includes content such as business processes, roles and responsibilities, policies, business rules, and authorization information. Process modeling standardizes and organizes the same or similar processes, extracts customers, products, and channels as variable factors, and uses standardized language to describe the business processes in a structured and standardized manner.

[0057] Business domain: A business domain is a set of business processes that cover planning, execution, and management. It utilizes the internal professional capabilities and external presentation capabilities of business components to meet customer requirements and realize customer value. Each business domain is a combination of enterprise-level perspectives unified activities based on specific business purposes, reflecting the real situation of the business.

[0058] Third-level activity: Each activity is initiated by a customer's event and describes the interaction process with the customer to fulfill customer needs or the work arrangement for internal management purposes.

[0059] Fourth-level task: A step executed by a role within a certain period of time, with a high degree of functional coupling within each task.

[0060] Fifth-level step: Describes specific business rules.

[0061] The current process modeling system includes business models such as value chain, business domain, third-level activity, fourth-level task, and fifth-level step. Among them, one third-level activity may correspond to multiple fourth-level tasks, and one fourth-level task will correspond to multiple fifth-level steps; other third-level activities can correspond to the same fourth-level tasks and the same multiple fifth-level steps. Therefore, the process modeling system contains a large number of related business models. In process modeling, when multiple users submit modeling tasks simultaneously, if there are intersections among the business models such as business domain, business value, third-level activity, fourth-level task, and fifth-level step in the submitted multiple modeling tasks, the modeling tasks are not allowed to be submitted after being judged by the process modeling system, and they are only allowed to be submitted when there is no intersection.

[0062] In the process of implementing the inventive concept of the present disclosure, the inventors found that there are at least the following problems in the related technologies: The process modeling system in the related technologies includes a large number of business models, the probability of the same business model existing between different modeling tasks is relatively high, and when there is a conflict in the business model, the modeling task cannot be executed, which affects the user experience and modeling efficiency. At the same time, users cannot know under what circumstances submitting a modeling task will not result in a conflict, thus affecting the user experience.

[0063] In view of this, in response to the above technical problems, the present disclosure records business models that conflict in multiple modeling tasks, determines target users from multiple users according to the conflicting business models and preset rules, and preferentially processes the modeling tasks submitted by the target users, thereby solving the technical problem that modeling tasks cannot be executed when there are business model conflicts between different modeling tasks, and improving the modeling efficiency.

[0064] Specifically, an embodiment of the present disclosure provides a request processing method for process modeling, including: receiving modeling task requests submitted by M users, where the modeling task requests include modeling data, and M≥2; in the case of determining that there is identical modeling data in the modeling task requests submitted by the M users, recording the identical modeling data to obtain intersection data; determining target users from the M users based on the preset rules according to the intersection data; and processing the modeling task requests submitted by the target users.

[0065] It should be noted that the request processing method and device for process modeling provided in the embodiments of the present disclosure can be used in the field of artificial intelligence. The request processing method and device for process modeling provided in the embodiments of the present disclosure can also be used in any field other than the field of artificial intelligence, such as the financial field. The application field of the request processing method and device for process modeling provided in the embodiments of the present disclosure is not limited.

[0066] In the technical solution of the present disclosure, before obtaining or collecting user personal information, the authorization or consent of the user is obtained.

[0067] In the technical solution of the present disclosure, the processing of data such as acquisition, collection, storage, use, processing, transmission, provision, disclosure, and application complies with the provisions of relevant laws and regulations, takes necessary confidentiality measures, and does not violate public order and good customs.

[0068] Figure 1 Schematically shows an application scenario diagram of a request processing method, device, device, medium, and program product for process modeling according to an embodiment of the present disclosure.

[0069] As Figure 1 shown, the application scenario 100 according to this embodiment may include a network, terminal devices, and a server. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0070] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Process modeling systems can be installed on terminal devices 101, 102, and 103 for process modeling.

[0071] Terminal devices 101, 102, and 103 can be various electronic devices with a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop computers, and desktop computers, etc.

[0072] Server 105 can be a server providing various services, such as a background management server (only for example) that supports the websites browsed by users using terminal devices 101, 102, and 103. The background management server can analyze and process data such as received user requests, and feedback the processing results (such as modeling tasks according to user requests) to the terminal devices.

[0073] It should be noted that the request processing method for process modeling provided by the embodiments of the present disclosure can generally be executed by server 105. Correspondingly, the request processing device for process modeling provided by the embodiments of the present disclosure can generally be set in server 105. The request processing method for process modeling provided by the embodiments of the present disclosure can also be executed by a server or a server cluster different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105. Correspondingly, the request processing device for process modeling provided by the embodiments of the present disclosure can also be set in a server or a server cluster different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105. Alternatively, the request processing method for process modeling provided by the embodiments of the present disclosure can also be executed by terminal device 101, 102, or 103, or can also be executed by other terminal devices different from terminal devices 101, 102, or 103. Correspondingly, the request processing device for process modeling provided by the embodiments of the present disclosure can also be set in terminal device 101, 102, or 103, or set in other terminal devices different from terminal devices 101, 102, or 103.

[0074] For example, the modeling data may originally be stored in any one of the terminal devices 101, 102, or 103 (e.g., terminal device 101, but not limited thereto), or stored on an external storage device and can be imported into the terminal device 101. Then, the terminal device 101 may locally execute the request processing method for process modeling provided by the embodiments of the present disclosure, or send the modeling data to other terminal devices, servers, or server clusters, and the other terminal devices, servers, or server clusters that receive the modeling data set execute the request processing method for process modeling provided by the embodiments of the present disclosure.

[0075] It should be understood that Figure 1 the numbers of terminal devices, networks, and servers in

[0076] are merely illustrative. According to the implementation requirements, there may be any number of terminal devices, networks, and servers. Figure 1 Based on the Figures 2 to 4 scenario described below, the request processing method for process modeling of the disclosed embodiments will be described in detail through

[0077] Figure 2 FIG. schematically shows a flowchart of a request processing method for process modeling according to an embodiment of the present disclosure.

[0078] As Figure 2 shown, the request processing method for process modeling of this embodiment includes operations S210 to S240, and the request processing method for process modeling may be executed by a server.

[0079] In operation S210, receive a modeling task request submitted by M users, where the modeling task request includes modeling data and M≥2.

[0080] According to an embodiment of the present disclosure, the business model in the process modeling system may include a value chain, business domains, secondary processes, tertiary activities, quaternary tasks, quinary steps, business components, etc., and the business model has a tree structure. For example, the value chain branches to form multiple business domains, the business domains continue to branch corresponding to multiple tertiary activities, the tertiary activities continue to branch corresponding to multiple quaternary tasks, and the quaternary tasks continue to branch corresponding to multiple quinary steps to form a tree structure. More specifically, one value chain in the process modeling system may correspond to multiple business domains, one business domain may correspond to multiple tertiary activities, one tertiary activity may correspond to multiple quaternary tasks, one quaternary task may correspond to multiple quinary steps, and one quinary step may correspond to multiple business components; at the same time, multiple tertiary activities may also correspond to the same quaternary task, and multiple quaternary tasks may also correspond to the same quinary step. For example, value chain A corresponds to three business domains B1, B2, and B3; business domain B1 corresponds to three secondary processes C1, C2, and C3, and business domain B2 corresponds to three secondary processes C4, C5, and C6; secondary process C1 corresponds to two tertiary activities D1 and D2, and secondary process C2 corresponds to two tertiary activities D3 and D4; tertiary activity D2 corresponds to two quaternary tasks E1 and E2, tertiary activity D3 corresponds to one quaternary task E3, and tertiary activity D4 corresponds to one quaternary task E4; quaternary task E1 corresponds to two quinary steps F1 and F2, and quaternary task E2 corresponds to two quinary steps F3 and F4, thus forming a tree structure.

[0081] In one embodiment, the process modeling system may include 7 value chains, 1190 business domains, 1436 tertiary activities, 6353 quaternary tasks, and tens of thousands of quinary steps. Therefore, when using the process modeling system for modeling tasks, the probability of conflicts occurring between business models is relatively high.

[0082] According to an embodiment of the present disclosure, the modeling task request may include, for example, a request submitted by a user for adding a model, a request for maintaining a model, etc. The modeling data may include business models such as a value chain, business domains, secondary processes, tertiary activities, quaternary tasks, quinary steps, business components, etc.

[0083] According to an embodiment of the present disclosure, receiving modeling task requests submitted by M users may include M users simultaneously editing the model to be added or maintained on the interface of the process modeling system of the terminal. After the M users finish editing, they simultaneously click to submit the modeling task request online and send the modeling data in the modeling task request to the server for processing.

[0084] In operation S220, in the case of determining that there is the same modeling data in the modeling task requests submitted by the above M users, record the same modeling data to obtain intersection data.

[0085] According to an embodiment of the present disclosure, the same modeling data may include, for example, at least two users submitting the same business model. For example, in the modeling data submitted by User A, the first business model is included, and at the same time, in the modeling data submitted by User B, the first business model is also included. Then, the first business model is the same modeling data.

[0086] According to an embodiment of the present disclosure, the intersection data may include, for example, all the business models with intersections in the modeling data submitted by M users. For example, in the modeling data submitted by User A, the first business model and the second business model are included. At the same time, in the modeling data submitted by User B, the first business model is included. In the modeling data submitted by User C, the first business model, the second business model, and the third business model are included. Since the first business model is simultaneously present in the modeling data of User A and User B, the first business model is one of the business models with intersections. Since the second business model is simultaneously present in the modeling data of User A and User C, the second business model is also a business model with intersections. Since the first business model is simultaneously present in the modeling data of User B and User C, the first business model is another business model with intersections. At this time, the intersection data includes the first business model, the second business model, and the first business model.

[0087] According to an embodiment of the present disclosure, in the case where there is no same modeling data in the modeling task requests submitted by the above M users, the modeling task requests submitted by the M users are processed separately.

[0088] In operation S230, based on the above intersection data, target users are determined from the above M users according to a preset rule.

[0089] According to an embodiment of the present disclosure, the preset rule may include, for example, determining the occupancy value of a user according to the intersection data, and taking the user with the largest occupancy value as the target user.

[0090] According to an embodiment of the present disclosure, the occupancy value of a user may include, for example, the number of business models included in the intersection data. For example, if the modeling data submitted by User A includes 2 business models in the intersection data, then the occupancy value of User A is 2; if the modeling data submitted by User B includes 3 business models in the intersection data, then the occupancy value of User B is 3; if the modeling data submitted by User C includes 4 business models in the intersection data, then the occupancy value of User C is 4. Since the occupancy value corresponding to User C is the largest, User C can be taken as the target user.

[0091] In operation S240, the modeling task request submitted by the above target user is processed.

[0092] According to an embodiment of the present disclosure, the modeling data in the modeling task request is obtained, and the modeling task request submitted by the user is processed according to the modeling data processing template.

[0093] According to an embodiment of the present disclosure, by receiving modeling task requests submitted by M users, it is determined whether there is the same modeling data according to the modeling data in the modeling task requests. In the case where it is determined that there is the same modeling data in the modeling task requests submitted by M users, the same modeling data is recorded to obtain intersection data; target users are determined from the M users based on a preset rule according to the intersection data; the modeling task requests submitted by the target users are processed. By optimizing the modeling method, it is supported that partial submission of modeling data can be performed when the modeling data submitted by multiple users has the same modeling data, so that the modeling task can be smoothly executed, improving the user experience and modeling efficiency. At least partially solve the technical problem that the modeling task cannot be executed when multiple submitted modeling tasks have the same modeling data, thus affecting the user experience and modeling efficiency.

[0094] According to an embodiment of the present disclosure, determining the target users from the M users based on the preset rule according to the intersection data includes: for each user among the M users, determining an occupancy value corresponding to the user according to the intersection data to obtain M such occupancy values; determining the maximum occupancy value among the M occupancy values to obtain a target occupancy value; determining the user corresponding to the target occupancy value as the target user.

[0095] According to an embodiment of the present disclosure, by determining the occupancy value corresponding to each user and taking the user with the largest occupancy value as the target user, the modeling task requests submitted by the target user are preferentially processed, so as to release more business models, reduce the probability of subsequent business model conflicts, and thus help improve the modeling efficiency.

[0096] According to an embodiment of the present disclosure, the M occupancy values are sorted from largest to smallest to obtain a sorting result, and the modeling task requests submitted by the M users are processed in sequence according to the sorting result. By determining the user occupancy value to control the preferential processing order, there is no need for the user to submit modeling data multiple times, which thus helps to further improve the modeling efficiency and also helps to improve the user experience.

[0097] According to an embodiment of the present disclosure, the above intersection data includes a business model and a category label of the above business model; the determining the occupancy value corresponding to the above user according to the above intersection data includes: determining the business model corresponding to the i-th user according to the above intersection data to obtain the i-th intersection model set, where 1≤i≤M; determining the i-th model category set corresponding to the i-th user according to the above i-th intersection model set and the above category label, where the above i-th model category set includes the category labels of the business models in the above i-th intersection model set; determining the users among the above M users who have an intersection with the above i-th user to obtain the i-th intersection user set, where the users who have an intersection with the above i-th user include the business models in the above i-th intersection model set in the modeling task requests submitted by the users; determining the above occupancy value corresponding to the i-th user according to the above i-th intersection model set, the above i-th model category set, and the above i-th intersection user set.

[0098] According to an embodiment of the present disclosure, the above category label includes one or more of value chain, business domain, secondary process, tertiary activity, quaternary task, quinary step, and business component.

[0099] According to an embodiment of the present disclosure, the business models in the process modeling system are classified according to value chain, business domain, secondary process, tertiary activity, quaternary task, quinary step, and business component to obtain category labels.

[0100] According to an embodiment of the present disclosure, the i-th intersection model set includes the business models corresponding to the i-th user in the intersection data. For example, the i-th intersection model set includes the first business model, the second business model, and the first business model.

[0101] According to an embodiment of the present disclosure, the i-th model category set may, for example, include the category labels corresponding to each business model in the i-th intersection model set. For example, the i-th intersection model set includes the first business model, the second business model, and the third business model, and the category label corresponding to the first business model is business domain, the category label corresponding to the second business model is quaternary task, and the category label corresponding to the third business model is quaternary task. Then the i-th model category set includes three category labels, namely business domain, quaternary task, and quaternary task.

[0102] According to an embodiment of the present disclosure, the i-th intersection user set includes the users who have an intersection with the i-th user. For example, the modeling data submitted by user A has the same business models as the modeling data submitted by user B and the modeling data submitted by user C, that is, the modeling data submitted by user B and the modeling data submitted by user C have the business models in the intersection model corresponding to user A. Then the intersection user set corresponding to user A includes user B and user C.

[0103] Figure 3The flowchart of the method for determining the target user according to an embodiment of the present disclosure is schematically shown.

[0104] As Figure 3 shown, in this embodiment, M = 3 is taken as an example, where the three users are User A, User B, and User C respectively. The method for determining the target user in this embodiment includes operations S301 to S307.

[0105] In operation S301, receive the modeling task requests submitted by User A, User B, and User C, where the modeling task requests include modeling data.

[0106] In operation S302, when it is determined that there is the same modeling data in the modeling task requests submitted by the three users, record the same modeling data to obtain intersection data.

[0107] In operation S303, determine the occupancy value corresponding to User A according to the intersection data to obtain the first occupancy value, where the method for determining the first occupancy value includes operations S3031 to S3034.

[0108] In operation S3031, determine the service model corresponding to User A according to the intersection data to obtain the first intersection model set.

[0109] In operation S3032, determine the first model category set corresponding to User A according to the first intersection model set and the category label.

[0110] In operation S3033, determine the users having an intersection with User A to obtain the first intersection user set.

[0111] In operation S3034, determine the first occupancy value corresponding to User A according to the first intersection model set, the first model category set, and the first intersection user set.

[0112] In operation S304, determine the occupancy value corresponding to User B according to the intersection data to obtain the second occupancy value, where the method for determining the second occupancy value includes operations S3041 to S3044.

[0113] In operation S3041, determine the service model corresponding to User B according to the intersection data to obtain the second intersection model set.

[0114] In operation S3042, determine the second model category set corresponding to User B according to the second intersection model set and the category label.

[0115] In operation S3043, determine the users having an intersection with User B to obtain the second intersection user set.

[0116] In operation S3044, determine a second occupancy value corresponding to user B according to the second intersection model set, the second model category set, and the second intersection user set.

[0117] In operation S305, determine an occupancy value corresponding to user C according to the intersection data to obtain a third occupancy value. The method for determining the third occupancy value includes operations S3051 to S3054.

[0118] In operation S3051, determine a service model corresponding to user C according to the intersection data to obtain a third intersection model set.

[0119] In operation S3052, determine a third model category set corresponding to user C according to the third intersection model set and the category label.

[0120] In operation S3053, determine the users having an intersection with user C to obtain a third intersection user set.

[0121] In operation S3054, determine a third occupancy value corresponding to user C according to the third intersection model set, the third model category set, and the third intersection user set.

[0122] In operation S306, determine the maximum occupancy value among the first occupancy value, the second occupancy value, and the third occupancy value to obtain a target occupancy value.

[0123] In operation S307, determine the user corresponding to the target occupancy value as the target user.

[0124] According to an embodiment of the present disclosure, the above request processing method for process modeling further includes: removing duplicates from the duplicate service models in the above i-th intersection model set to obtain a deduplicated i-th intersection model set; removing duplicates from the duplicate category labels in the above i-th model category set to obtain a deduplicated i-th model category set; the above determining the above occupancy value corresponding to the above i-th user according to the above i-th intersection model set, the above i-th model category set, and the above i-th intersection user set includes: determining the above occupancy value corresponding to the above i-th user according to the above i-th intersection model set, the deduplicated i-th intersection model set, the above i-th model category set, the deduplicated i-th model category set, and the above i-th intersection user set.

[0125] According to an embodiment of the present disclosure, for example, when removing duplicates from the i-th intersection model set, if the i-th intersection model set includes a first service model, a second service model, and the first service model, then remove the duplicate first service model from the i-th intersection model set. The obtained deduplicated i-th intersection model set includes the first service model and the second service model.

[0126] According to an embodiment of the present disclosure, for deduplication processing of the i-th model category set, for example, if the i-th model category intersection includes a business area, a fourth-level task, and a fourth-level task, then deduplication processing is performed on the i-th model category set to remove the duplicate category label of the fourth-level task, and the deduplicated i-th model category set obtained includes the business area and the fourth-level task.

[0127] According to an embodiment of the present disclosure, determining the occupancy value corresponding to the i-th user based on the above-mentioned i-th intersection model set, the above-mentioned deduplicated i-th intersection model set, the above-mentioned i-th model category set, the above-mentioned deduplicated i-th model category set, and the above-mentioned i-th intersection user set includes: determining the number of i-th intersection users corresponding to the i-th user according to the above-mentioned i-th intersection user set; determining the ratio of the number of i-th intersection users and the number of M users to obtain a first occupancy value; determining the number of i-th intersection models corresponding to the i-th user according to the above-mentioned i-th intersection model set; determining the ratio of the number of i-th intersection models and the number of deduplicated i-th intersection models to obtain a second occupancy value; determining the number of i-th model categories corresponding to the i-th user according to the above-mentioned i-th model category set; determining the ratio of the number of i-th model categories and the number of deduplicated i-th model categories to determine a third occupancy value; determining the occupancy value corresponding to the i-th user according to the above-mentioned first occupancy value, the above-mentioned second occupancy value, and the above-mentioned third occupancy value.

[0128] According to an embodiment of the present disclosure, the occupancy value corresponding to user A can be expressed by the following formula:

[0129]

[0130] Wherein,

[0131] A z represents the occupancy value of user A;

[0132] A1 represents the number of intersection users corresponding to user A;

[0133] M represents the total number of users with intersections;

[0134] A2 represents the number of intersection models corresponding to user A;

[0135] A'2 represents the number of deduplicated intersection models corresponding to user A;

[0136] A3 represents the number of model categories corresponding to user A;

[0137] A'3 represents the number of deduplicated model categories corresponding to user A.

[0138] Figure 4 Schematically shows a flowchart of a request processing method for process modeling according to another embodiment of the present disclosure.

[0139] As shown Figure 4 in the figure, the request processing method for process modeling in this embodiment includes operations S401 to S408.

[0140] In operation S401, a modeling task request submitted by M users is received, where the modeling task request includes modeling data, and M ≥ 2.

[0141] In operation S402, it is determined whether there is the same modeling data among the modeling task requests submitted by M users. If there is the same modeling data among the modeling task requests submitted by M users, operation S403 is executed; if there is no same modeling data among the modeling task requests submitted by M users, operation S408 is executed.

[0142] In operation S403, the same modeling data among the modeling task requests submitted by M users is recorded to obtain intersection data.

[0143] In operation S404, for each of the M users, an occupancy value corresponding to the user is determined according to the intersection data to obtain M occupancy values.

[0144] In operation S405, the maximum occupancy value among the M occupancy values is determined to obtain a target occupancy value.

[0145] In operation S406, the user corresponding to the target occupancy value is determined as the target user.

[0146] In operation S407, the modeling task is processed according to the modeling data submitted by the target user.

[0147] In operation S408, the modeling task requests submitted by M users are processed.

[0148] According to the embodiment of the present disclosure, by receiving the modeling task requests submitted by M users, it is determined whether there is the same modeling data according to the modeling data in the modeling task requests. When it is determined that there is the same modeling data among the modeling task requests submitted by M users, the same modeling data is recorded to obtain intersection data; the target user is determined from the M users based on the intersection data according to a preset rule; the modeling task request submitted by the target user is processed. By optimizing the modeling method, it is supported that partial submission of modeling data can be performed when the modeling data submitted by multiple users has the same modeling data, improving the modeling efficiency. At least partially solve the technical problem that when multiple submitted modeling tasks have the same modeling data, the modeling tasks cannot be processed, thus affecting the modeling efficiency.

[0149] It should be noted that, unless it is explicitly stated that there is a sequence of execution between different operations shown in the flowchart in the embodiments of the present disclosure, or there is a sequence of execution between different operations in technical implementation, otherwise, the execution order between multiple operations may not be prioritized, and multiple operations may also be executed simultaneously.

[0150] Based on the above-mentioned request processing method for process modeling, the present disclosure also provides a request processing device for process modeling. Figure 5 The device is described in detail.

[0151] Figure 5 The structural block diagram of the request processing device for process modeling according to an embodiment of the present disclosure is schematically shown.

[0152] like Figure 5 As shown, the request processing device 500 for process modeling in this embodiment includes a receiving module 510 , a recording module 520 , a determining module 530 and a processing module 540 .

[0153] The receiving module 510 is configured to receive modeling task requests submitted by M users, wherein the modeling task requests include modeling data, and M≥2. In one embodiment, the receiving module 510 may be configured to perform the operation S210 described above, which will not be described in detail here.

[0154] The recording module 520 is used to record the same modeling data when determining that the modeling task requests submitted by the M users have the same modeling data to obtain intersection data. In one embodiment, the recording module 520 can be used to perform the operation S220 described above, which will not be repeated here.

[0155] The determination module 530 is configured to determine the target user from the M users based on the intersection data and a preset rule. In one embodiment, the determination module 530 may be configured to execute the operation S230 described above, which will not be described in detail herein.

[0156] The processing module 540 is used to process the modeling task request submitted by the target user. In one embodiment, the processing module 540 can be used to perform the operation S240 described above, which will not be repeated here.

[0157] Figure 6 The structural block diagram of the determination module according to an embodiment of the present disclosure is schematically shown.

[0158] like Figure 6 As shown, the determination module 530 of this embodiment includes a first determination submodule 531 , a second determination submodule 532 and a third determination submodule 533 .

[0159] The first determination sub-module 531 is configured to determine, for each of the M users, an occupancy value corresponding to the user according to the intersection data, and obtain M such occupancy values.

[0160] The second determination sub-module 532 is configured to determine the maximum occupancy value among the M occupancy values to obtain a target occupancy value.

[0161] The third determination sub-module 533 is configured to determine that the user corresponding to the target occupancy value is the target user.

[0162] According to an embodiment of the present disclosure, the intersection data includes a service model and a category label of the service model.

[0163] According to an embodiment of the present disclosure, the first determination sub-module includes: a first determination unit, a second determination unit, a third determination unit, and a fourth determination unit.

[0164] The first determination unit is configured to determine a service model corresponding to the i-th user according to the intersection data to obtain an i-th intersection model set, where 1 ≤ i ≤ M.

[0165] The second determination unit is configured to determine an i-th model category set corresponding to the i-th user according to the i-th intersection model set and the category label, where the i-th model category set includes the category label of the service model in the i-th intersection model set.

[0166] The third determination unit is configured to determine the users among the M users who have an intersection with the i-th user to obtain an i-th intersection user set, where the users who have an intersection with the i-th user include the service models in the i-th intersection model set in the modeling task requests submitted by the users.

[0167] The fourth determination unit is configured to determine the occupancy value corresponding to the i-th user according to the i-th intersection model set, the i-th model category set, and the i-th intersection user set.

[0168] According to an embodiment of the present disclosure, the first determination sub-module further includes: a first deduplication unit and a second deduplication unit.

[0169] The first deduplication unit is configured to perform deduplication processing on the duplicate service models in the i-th intersection model set to obtain a deduplicated i-th intersection model set.

[0170] The second deduplication unit is configured to perform deduplication processing on the duplicate category labels in the i-th model category set to obtain a deduplicated i-th model category set.

[0171] According to an embodiment of the present disclosure, the fourth determination unit is further configured to determine the occupancy value corresponding to the i-th user according to the above-mentioned i-th intersection model set, the deduplicated i-th intersection model set, the above-mentioned i-th model category set, the deduplicated i-th model category set, and the above-mentioned i-th intersection user set.

[0172] According to an embodiment of the present disclosure, the above-mentioned fourth determination unit includes: a first determination subunit, a second determination subunit, a third determination subunit, a fourth determination subunit, a fifth determination subunit, a sixth determination subunit, and a seventh determination subunit.

[0173] The first determination subunit is configured to determine the number of i-th intersection users corresponding to the i-th user according to the above-mentioned i-th intersection user set.

[0174] The second determination subunit is configured to determine the ratio of the number of the i-th intersection users to the number of the M users to obtain a first occupancy value.

[0175] The third determination subunit is configured to determine the number of i-th intersection models corresponding to the i-th user according to the above-mentioned i-th intersection model set.

[0176] The fourth determination subunit is configured to determine the ratio of the number of the i-th intersection models to the number of the deduplicated i-th intersection models to obtain a second occupancy value.

[0177] The fifth determination subunit is configured to determine the number of i-th model categories corresponding to the i-th user according to the above-mentioned i-th model category set.

[0178] The sixth determination subunit is configured to determine a third occupancy value according to the number of the i-th model categories and the number of the deduplicated i-th model categories.

[0179] The seventh determination subunit is configured to determine the above-mentioned occupancy value corresponding to the i-th user according to the above-mentioned first occupancy value, the above-mentioned second occupancy value, and the above-mentioned third occupancy value.

[0180] According to an embodiment of the present disclosure, the above-mentioned category labels include one or more of value chain, business domain, secondary process, tertiary activity, quaternary task, quinary step, and business component.

[0181] Any of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure, or at least part of the functions of any of them, can be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure can be split into multiple modules for implementation. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure can be at least partially implemented as a hardware circuit, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by any other reasonable way of integrating or packaging circuits, such as hardware or firmware, or can be implemented in any one of the three implementation manners of software, hardware, and firmware, or in an appropriate combination of any several of them. Alternatively, one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding functions can be executed.

[0182] According to the embodiments of the present disclosure, any of the receiving module 510, the recording module 520, the determining module 530, and the processing module 540 can be combined and implemented in one module, or any one of them can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to the embodiments of the present disclosure, at least one of the receiving module 510, the recording module 520, the determining module 530, and the processing module 540 can be at least partially implemented as a hardware circuit, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by any other reasonable way of integrating or packaging circuits, such as hardware or firmware, or can be implemented in any one of the three implementation manners of software, hardware, and firmware, or in an appropriate combination of any several of them. Alternatively, at least one of the receiving module 510, the recording module 520, the determining module 530, and the processing module 540 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding functions can be executed.

[0183] It should be noted that the part of the request processing device for process modeling in the embodiments of the present disclosure corresponds to the part of the request processing method for process modeling in the embodiments of the present disclosure. For the description of the part of the request processing device for process modeling, please refer to the part of the request processing method for process modeling, and details will not be repeated here.

[0184] Figure 7A block diagram of an electronic device suitable for implementing a request processing method for process modeling according to an embodiment of the present disclosure is schematically shown.

[0185] As Figure 7 shown, the electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage section 708 into a random access memory (RAM) 703. The processor 701 can include, for example, a general-purpose microprocessor (e.g., CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 can also include on-board memory for caching purposes. The processor 701 can include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0186] In the RAM 703, various programs and data required for the operation of the electronic device 700 are stored. The processor 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. The processor 701 performs various operations of the method flow according to an embodiment of the present disclosure by executing the programs in the ROM 702 and / or the RAM 703. It should be noted that the program can also be stored in one or more memories other than the ROM 702 and the RAM 703. The processor 701 can also perform various operations of the method flow according to an embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0187] According to an embodiment of the present disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, and the input / output (I / O) interface 705 is also connected to the bus 704. The electronic device 700 may further include one or more of the following components connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, a modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed so that a computer program read from it can be installed into the storage section 708 as needed.

[0188] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the foregoing embodiments; or may exist separately without being assembled into the device / apparatus / system. The foregoing computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to the embodiments of the present disclosure is implemented.

[0189] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the foregoing ROM 702 and / or RAM 703 and / or one or more memories other than ROM 702 and RAM 703.

[0190] An embodiment of the present disclosure further includes a computer program product, which includes a computer program, and the computer program includes program code for executing the method shown in the flowchart. When the computer program product runs in a computer system, the program code is used to cause the computer system to implement the request processing method for process modeling provided by the embodiments of the present disclosure.

[0191] When the computer program is executed by the processor 701, the above functions defined in the system / apparatus of the embodiments of the present disclosure are executed. According to an embodiment of the present disclosure, the foregoing systems, apparatuses, modules, units, etc. may be implemented by computer program modules.

[0192] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices and magnetic storage devices. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium, and is downloaded and installed through the communication part 709, and / or installed from the removable medium 711. The program code included in the computer program may be transmitted by any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

[0193] In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, the above functions defined in the system of the embodiments of the present disclosure are executed. According to the embodiments of the present disclosure, the above-described systems, devices, apparatuses, modules, units, etc. can be implemented by computer program modules.

[0194] According to the embodiments of the present disclosure, the program code for executing the computer program provided by the embodiments of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include, but are not limited to, such as Java, C++, Python, the "C" language, or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., by connecting through the Internet using an Internet service provider).

[0195] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0196] Those skilled in the art can understand that the features recited in the various embodiments and / or claims of the present disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly recited in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features recited in the various embodiments and / or claims of the present disclosure can be combined and combined in various ways. All such combinations and / or combinations fall within the scope of the present disclosure.

[0197] The embodiments of the present disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments have been described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and all such substitutions and modifications should fall within the scope of the present disclosure.

Claims

1. A request processing method for process modeling, comprising: Receiving modeling task requests submitted by M users, where the modeling task requests include modeling data, and M ≥ 2; When it is determined that there is the same modeling data in the modeling task requests submitted by the M users, recording the same modeling data to obtain intersection data, where the intersection data includes at least one business model; Determining target users from the M users based on the intersection data according to a preset rule, where the preset rule includes determining the occupancy value of a user according to the intersection data and taking the user with the largest occupancy value as the target user, and the occupancy value of the user is determined according to the number of business models in the intersection data included in the modeling data submitted by the user; and Processing the modeling task request submitted by the target user.

2. The method according to claim 1, wherein The determining target users from the M users based on the intersection data according to a preset rule includes: For each of the M users, determining the occupancy value corresponding to the user according to the intersection data to obtain M occupancy values; Determining the maximum occupancy value among the M occupancy values to obtain a target occupancy value; Determining the user corresponding to the target occupancy value as the target user.

3. The method according to claim 2, wherein The intersection data includes business models and category labels of the business models; The determining the occupancy value corresponding to the user according to the intersection data includes: Determining the business models corresponding to the i-th user according to the intersection data to obtain an i-th intersection model set, where 1 ≤ i ≤ M; Determining an i-th model category set corresponding to the i-th user according to the i-th intersection model set and the category labels, where the i-th model category set includes the category labels of the business models in the i-th intersection model set; Determining the users among the M users who have an intersection with the i-th user to obtain an i-th intersection user set, where the users who have an intersection with the i-th user include the business models in the i-th intersection model set in the modeling task requests submitted by the users; Determining the occupancy value corresponding to the i-th user according to the i-th intersection model set, the i-th model category set, and the i-th intersection user set.

4. The method according to claim 3, further comprising: Removing duplicate business models in the i-th intersection model set to obtain a deduplicated i-th intersection model set; Removing duplicate category labels in the i-th model category set to obtain a deduplicated i-th model category set; The determining the occupancy value corresponding to the i-th user according to the i-th intersection model set, the i-th model category set, and the i-th intersection user set includes: Determining the occupancy value corresponding to the i-th user according to the i-th intersection model set, the deduplicated i-th intersection model set, the i-th model category set, the deduplicated i-th model category set, and the i-th intersection user set.

5. The method according to claim 4, wherein Determining the occupancy value corresponding to the i-th user based on the i-th intersection model set, the deduplicated i-th intersection model set, the i-th model category set, the deduplicated i-th model category set, and the i-th intersection user set includes: Determining the number of i-th intersection users corresponding to the i-th user according to the i-th intersection user set; Determining the ratio of the number of i-th intersection users to the number of M users to obtain a first occupancy value; Determining the number of i-th intersection models corresponding to the i-th user according to the i-th intersection model set; Determining the ratio of the number of i-th intersection models to the number of deduplicated i-th intersection models to obtain a second occupancy value; Determining the number of i-th model categories corresponding to the i-th user according to the i-th model category set; Determining a third occupancy value based on the number of i-th model categories and the number of deduplicated i-th model categories; Determining the occupancy value corresponding to the i-th user according to the first occupancy value, the second occupancy value, and the third occupancy value.

6. The method according to claim 3, wherein The category labels include one or more of value chain, business domain, secondary process, tertiary activity, quaternary task, quinary step, and business component.

7. A request processing apparatus for process modeling, comprising: A receiving module, configured to receive modeling task requests submitted by M users, where the modeling task requests include modeling data and M≥2; A recording module, configured to record the same modeling data when it is determined that there is the same modeling data in the modeling task requests submitted by the M users, to obtain intersection data, where the intersection data includes at least one business model; A determining module, configured to determine target users from the M users based on preset rules according to the intersection data, where the preset rules include determining the occupancy value of a user according to the intersection data and taking the user with the largest occupancy value as the target user, and the occupancy value of the user is determined according to the number of business models in the intersection data included in the modeling data submitted by the user; and A processing module, configured to process the modeling task request submitted by the target user.

8. An electronic device, comprising: One or more processors; A storage device, configured to store one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors are caused to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor is caused to execute the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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