Task allocation method, device and electronic equipment

Abstract

The present invention provides a task allocation method, device and electronic equipment, which relate to the field of automation technology, wherein the method includes: a task system responds to an allocation instruction of a target task and obtains a subject identification set of a task undertaking subject; calls a pre-set inter-system component to obtain status data of each task undertaking subject in the subject identification set from a status system, wherein the task system and the status system are isolated from each other; determines the acceptability status of each task undertaking subject based on the status data; and selects at least one task undertaking subject identification from the subject identification set as the undertaking node of the target task based on the acceptability status. This solution determines the acceptability status of each task undertaking subject based on the status data, and determines the undertaking node of the target task based on the acceptability status, which can avoid problems such as the task undertaking node being unable to process the target task in a timely manner after the task is assigned to the task undertaking node, and restarting the workflow, wasting time and human resources.

Description

Technical Field

[0001] The present application relates to the field of automation technology, and in particular to a task allocation method, device, and electronic device. Background Art

[0002] In existing task allocation systems, there is often an isolation between the task allocation system and the status system of the receiving node, which makes the task allocation system unable to effectively obtain the receiving status of each receiving node. This also makes the task allocation system often have unreasonable allocation plans when allocating tasks. For example: some receiving nodes are assigned too much tasks, some nodes are assigned too little tasks, and some nodes are assigned tasks when they are in the rest or maintenance stage. This will result in the tasks being unable to be effectively processed and the receiving capacity of the receiving nodes cannot be effectively utilized.

[0003] For example, in existing business management systems, each employee is typically assigned an account. Each collaborative work assignment is divided into multiple tasks. These tasks are then processed in a sequence based on their dependencies, forming a workflow for that task. Each task is treated as a process node in the workflow, and at least one employee is assigned to each process node as the handler. A process engine maintains each workflow, ensuring the orderly and efficient flow of tasks to each handler. If workflow X is transferred to employee A and employee A takes leave, another employee, B, will typically log in to employee A's account and handle the task for the current process node on his behalf.

[0004] However, in enterprises with high system or data security requirements, employee A's account can only be logged in by him personally, and no other employee B is allowed to log in. Therefore, if workflow X is transferred to employee A and employee A takes leave, there are three possible ways to handle workflow X without affecting employee A's leave: 1. Wait until employee A returns from leave. This approach may cause the processing time of the current node of workflow X to be too long, affecting the overall processing efficiency of workflow X; 2. A highly authorized administrator can terminate workflow X and re-initiate workflow Y, assigning a different handler to the current node. This approach requires handlers at previous nodes to re-process tasks already handled in workflow X, adding additional workload and wasting time and human resources.

[0005] There is no effective solution to the problem of irrational task allocation in existing task allocation systems, which leads to low task completion efficiency and waste of resources. Summary of the Invention

[0006] The purpose of this application is to provide a task allocation method, device and electronic device to solve the problem of "low task completion efficiency and waste of resources".

[0007] In order to solve the above technical problems, the first aspect of this specification provides a task allocation method, including: the task system receives an allocation instruction of a target task; in response to the allocation instruction, obtains a subject identification set of the task undertaking subject; calls a pre-set inter-system component to obtain status data of each task undertaking subject in the subject identification set from a status system, wherein the task system and the status system are isolated from each other; based on the status data, determines the acceptability status of each task undertaking subject in the subject identification set; based on the acceptability status of each task undertaking subject, selects at least one task undertaking subject identification from the subject identification set as the undertaking node of the target task.

[0008] In some embodiments, the acceptable state includes: a first state and a second state, wherein the first state is that the task can be accepted within a first predetermined period of time from the current time, and the second state is that the task cannot be accepted within the first predetermined period of time from the current time; accordingly, according to the acceptable state of each task undertaking entity, at least one task undertaking entity is selected from the entity identification set as the undertaking node of the target task, including: selecting the identifier of at least one task undertaking entity in the first state from the entity identification set as the undertaking node of the target task.

[0009] In some embodiments, selecting at least one task undertaking entity in the first state from the entity identification set as the undertaking node of the target task includes: obtaining the task saturation of each task undertaking entity in the first state in the entity identification set within a first predetermined time period from the current time; and selecting the identification of at least one task undertaking entity as the undertaking node of the target task in order of task saturation from low to high.

[0010] In some embodiments, the status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, based on the status data, the acceptability status of each task undertaking subject in the subject identification set is determined, including: when the start time of the time period in which the task undertaking subject cannot undertake the task is within the first time period, and the end time is not within the first time period, obtaining the estimated processing time of the target task; wherein the first time period is the first predetermined time period from the current time; judging whether the time from the current time to the start time is greater than the estimated processing time; when the time from the current time to the second predetermined time is greater than the estimated processing time, determining that the task undertaking subject is in the third state; accordingly, based on the acceptability status of each task undertaking subject, selecting at least one task undertaking subject from the subject identification set as the acceptance node of the target task, including: selecting at least one identifier of the task undertaking subject in the third state from the subject identification set as the acceptance node of the target task.

[0011] In some embodiments, the status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, based on the status data, the acceptability status of each task undertaking subject in the subject identification set is determined, including: when the start time of the time period in which the task undertaking subject cannot undertake the task is not within the first time period, but the end time is within the first time period, obtaining the estimated processing time of the target task; wherein the first time period is the first predetermined time from the current time; when the estimated processing time of the target task is less than the predetermined time threshold, determining that the task undertaking subject is in the third state; accordingly, based on the acceptability status of each task undertaking subject, selecting at least one task undertaking subject from the subject identification set as the acceptance node of the target task, including: selecting at least one identifier of the task undertaking subject in the third state from the subject identification set as the acceptance node of the target task.

[0012] In some embodiments, obtaining the estimated processing time of the target task includes: obtaining feature data of the target task; inputting the feature data of the target task into a pre-trained prediction model to predict the estimated processing time of the target task.

[0013] In some embodiments, the characteristic data of the target task is input into a pre-trained prediction model, and before the estimated processing time of the target task is predicted, the method also includes: classifying the task data stored in the database according to the type of task; wherein, tasks of the same type have the same type of characteristic data; the task data includes the characteristic data of the task and the processing time of the task; training the prediction model for each type of task according to the following method: obtaining multiple task data of a task type; using the processing time in the multiple task data as the output of the prediction model, and using the characteristic data in the multiple task data as the input of the prediction model, and training the prediction model.

[0014] In some embodiments, the status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, based on the status data, the acceptability status of each task undertaking subject in the subject identification set is determined, including: when the start time of the time period in which the task undertaking subject cannot undertake the task is not within the first time period, but the end time is within the first time period, obtaining the urgency of the target task; wherein the first time period is the first predetermined duration from the current time; when the urgency of the target task is lower than the predetermined degree threshold, determining that the task undertaking subject is in the third state; accordingly, based on the acceptability status of each task undertaking subject, selecting at least one task undertaking subject from the subject identification set as the acceptance node of the target task, including: selecting at least one identifier of the task undertaking subject in the third state from the subject identification set as the acceptance node of the target task.

[0015] In some embodiments, before selecting at least one task undertaking entity in the third state from the entity identification set as the undertaking node of the target task, it also includes: obtaining the task saturation of each task undertaking entity in the first state in the entity identification set within a first predetermined time period from the current time; when the task saturation of each task undertaking entity is greater than the predetermined saturation threshold, executing the selection of at least one task undertaking entity in the third state from the entity identification set as the undertaking node of the target task.

[0016] The second aspect of this specification provides a task allocation device, including: a receiving unit, used for the task system to receive the allocation instruction of the target task; an acquisition unit, used for obtaining a subject identification set of the task undertaking subject in response to the allocation instruction; a calling unit, used for calling a pre-set inter-system component to obtain the status data of each task undertaking subject in the subject identification set from the status system, wherein the task system and the status system are isolated from each other; a determination unit, used for determining the acceptability status of each task undertaking subject in the subject identification set based on the status data; and a selection unit, used for selecting the identification of at least one task undertaking subject from the subject identification set as the acceptance node of the target task based on the acceptability status of each task undertaking subject.

[0017] In some embodiments, the acceptable state includes: a first state and a second state, wherein the first state is that the task can be accepted within a first predetermined period of time from the current time, and the second state is that the task cannot be accepted within the first predetermined period of time from the current time; accordingly, the selection unit includes: a first selection sub-unit, for selecting the identifier of at least one task acceptance subject in the first state from the subject identifier set as the acceptance node of the target task.

[0018] In some embodiments, the first selection sub-unit includes: a first acquisition sub-unit, used to obtain the task saturation of each task undertaking subject in the first state in the subject identification set within a first predetermined time period from the current time; a second selection sub-unit, used to select the identification of at least one task undertaking subject as the undertaking node of the target task in order of task saturation from low to high.

[0019] In some embodiments, the status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, the determination unit includes: a second acquisition sub-unit, used to obtain the estimated processing time of the target task when the start time of the time period in which the task undertaking entity cannot undertake the task is within the first time period and the end time is not within the first time period; wherein the first time period is the first predetermined time period starting from the current time; a first determination sub-unit, used to determine that the task undertaking entity is in the third state when the time from the current time to the second predetermined time is greater than the estimated processing time; accordingly, the selection unit includes: a third selection sub-unit, used to select at least one identifier of the task undertaking entity in the third state from the entity identifier set as the undertaking node of the target task.

[0020] In some embodiments, the status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, the determination unit includes: a third acquisition sub-unit, used to obtain the estimated processing time of the target task when the start time of the time period in which the task undertaking entity cannot undertake the task is not within the first time period, and the end time is within the first time period; wherein the first time period is the first predetermined time period from the current time; a second determination sub-unit, used to determine that the task undertaking entity is in the third state when the estimated processing time of the target task is less than a predetermined time threshold; accordingly, the selection unit includes: a third selection sub-unit, used to select at least one identifier of the task undertaking entity in the third state from the entity identifier set as the undertaking node of the target task.

[0021] In some embodiments, the second acquisition subunit or the third acquisition subunit includes: a fourth acquisition subunit, used to acquire feature data of the target task; and a prediction subunit, used to input the feature data of the target task into a pre-trained prediction model to predict the estimated processing time of the target task.

[0022] In some embodiments, it also includes: a classification unit, which is used to classify the task data stored in the database according to the type of task; wherein, tasks of the same type have the same type of feature data; the task data includes the feature data of the task and the processing time of the task; a training unit, which is used to train a prediction model for each type of task according to the following method: obtain multiple task data of a task type; use the processing time in the multiple task data as the output of the prediction model, and use the feature data in the multiple task data as the input of the prediction model to train the prediction model.

[0023] In some embodiments, the status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, the determination unit includes: a fifth acquisition sub-unit, used to obtain the urgency of the target task when the start time of the time period in which the task undertaking entity cannot undertake the task is not within the first time period, and the end time is within the first time period; wherein the first time period is the first predetermined duration from the current time; a third determination sub-unit, used to determine that the task undertaking entity is in the third state when the urgency of the target task is lower than a predetermined degree threshold; accordingly, the selection unit includes: a third selection sub-unit, used to select at least one identifier of the task undertaking entity in the third state from the entity identifier set as the undertaking node of the target task.

[0024] In some embodiments, it also includes: a sixth acquisition sub-unit, used to obtain the task saturation of each task undertaking entity in the first state in the entity identification set within a first predetermined time period from the current time; when the task saturation of each task undertaking entity is greater than the predetermined saturation threshold, the third selection sub-unit executes the selection of at least one identification of the task undertaking entity in the third state from the entity identification set as the undertaking node of the target task.

[0025] The third aspect of this specification provides an electronic device, comprising: a memory and a processor, wherein the processor and the memory are communicatively connected to each other, the memory stores computer instructions, and the processor implements the steps of any one of the methods described in the first aspect by executing the computer instructions.

[0026] A fourth aspect of this specification provides a computer storage medium, wherein the computer storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the steps of any one of the methods described in the first aspect are implemented.

[0027] A fifth aspect of this specification provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of any one of the methods described in the first aspect.

[0028] The above-mentioned task allocation method sets up an inter-system component between the task system and the status system which were originally isolated from each other, so that the task system can obtain the status data of the task undertaking subject from the status system; the above-mentioned task allocation method further determines the acceptance status of each task undertaking subject based on the status data of the task undertaking subject, and then determines the acceptance node of the target task based on the acceptance status of each task undertaking subject, which can avoid the problem that after the target task is assigned to a task undertaking node, the task undertaking node cannot process it in time, restarting the workflow wastes time and human resources, etc., that is, solves the problems of low task completion efficiency and waste of resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the implementation methods of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the implementation methods or the description of the prior art. Obviously, the drawings described below are only some implementation methods recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0030] Figure 1 A flowchart showing an embodiment of the task allocation method provided in this specification is shown;

[0031] Figure 2A schematic diagram showing an implementation of obtaining state data from a state system through an inter-system component;

[0032] Figure 3A and Figure 3B Two schematic diagrams of the third state are shown;

[0033] Figure 4 A schematic diagram showing the undertaking nodes of the determined target tasks and their undertaking status is shown;

[0034] Figure 5 A flowchart showing another embodiment of the task allocation method provided in this specification is shown;

[0035] Figure 6 A flowchart showing another embodiment of the task allocation method provided in this specification;

[0036] Figure 7 A flowchart showing another embodiment of the task allocation method provided in this specification;

[0037] Figure 8 A flowchart showing another embodiment of the task allocation method provided in this specification is shown;

[0038] Figure 9A A principle block diagram of an embodiment of a task allocation device provided in this specification is shown;

[0039] Figure 9B A principle block diagram showing another embodiment of the task allocation device provided in this specification is shown;

[0040] Figure 9C A principle block diagram showing another embodiment of the task allocation device provided in this specification is shown;

[0041] Figure 10 A schematic structural diagram of an electronic device according to an embodiment of this specification is shown. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the technical solutions in this application, the following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0043] Existing enterprises typically have multiple departments. Accordingly, the business management systems they use often include multiple subsystems, such as human resources, finance, and task allocation. These subsystems are technically isolated from each other, meaning data cannot be shared between them to ensure data security.

[0044] Based on this, existing task allocation subsystems can only obtain each employee's task processing permissions from the task allocation system when assigning tasks, for example, which employees have processing permissions for Task Y. Typically, each employee's task processing permissions are pre-set in the task system. This often leads to irrational allocation schemes in existing task allocation systems. For example, some receiving nodes are assigned too many tasks, while others are assigned too few, or even nodes are assigned tasks while they are resting or undergoing maintenance. This results in tasks not being processed effectively and the receiving nodes' capacity not being effectively utilized.

[0045] For example, a job includes six tasks that are executed sequentially. The workflow X corresponding to the job includes six process nodes A, B, C, D, E, and F that are executed sequentially, where each process node corresponds to a task.

[0046] The task corresponding to each process node is handled by a staff member in a position. Each position includes at least one staff member, and some positions include multiple staff members. For example, the task corresponding to process node A is handled by the staff member in position a. Position a may have three staff members a1, a2, and a3. Each staff member can handle the task corresponding to process node A. The task corresponding to process node B is handled by the staff member in position b. Position b may have four staff members b1, b2, b3, and b4. Each staff member can handle the task corresponding to process node B. The same applies to other tasks.

[0047] When assigning a task corresponding to process node B, the existing task system randomly selects one of the four staff members in position B (those with permission to handle task B) to handle task B. If a staff member B2 in position B takes leave, the assigning staff member must be specifically informed. However, even if informed, the assigning staff member may forget about B2's leave and assign the task corresponding to process node B to the staff member B2 who is on leave.

[0048] In enterprises with high system or data security requirements, worker B2's account can only be logged in personally; other workers B1 or B3 are not allowed to log in. Therefore, if worker B2 takes leave when workflow X is transferred to worker B2, there are three possible approaches to workflow X, provided that this does not affect B2's leave: 1. Wait until worker B2 returns from leave. This approach may cause the processing time of the current process node in workflow X to be too long, affecting the overall processing efficiency of workflow X. 2. A highly authorized administrator can terminate workflow X and re-initiate workflow Y, assigning a different handler to the task corresponding to process node B. This approach requires handlers at all process nodes before process node B to reprocess the tasks already processed in workflow X, adding additional workload and wasting human resources.

[0049] In this regard, this specification provides a task allocation method. Figure 1 As shown, the method includes the following steps:

[0050] S110: The task system receives an assignment instruction for a target task.

[0051] In some embodiments, before a workflow is initiated, a task assignor uniformly assigns the individuals to handle each task in the workflow. The target task assignment instructions can be issued by the task assignor within the system. For example, before the aforementioned workflow X is initiated, the task assignor uniformly assigns workers a1, b2, c4, d2, e3, and f5.

[0052] In some embodiments, after a workflow is initiated and a task at a process node is completed, the handler of that process node must select the handler for the next process node. The task at the next process node is the target task to be assigned. The target task assignment instruction is provided by the task completer of the process node in the system. For example, in the aforementioned workflow X, after task a1 completes task A, the system selects handler b3 for task B (i.e., the next task).

[0053] In some embodiments, the target task assignment instruction may also be automatically given by the system without the need for manual operation in the system.

[0054] S120: In response to the allocation instruction, obtain a subject identification set of the task undertaking subject.

[0055] The task undertaking entity described in this application can be a staff member, a machine, a server, an electronic device, etc. Any entity with physical processing capabilities (for example, packaging products) or data processing capabilities can serve as a task undertaking entity. In the above embodiment related to workflow X, the task undertaking entity is a staff member.

[0056] These task undertaking entities perform their work according to the workflow.

[0057] Different task undertaking entities have different identifiers, and the entity identifier is used to represent a task undertaking entity.

[0058] In some embodiments, the task undertaking entity in S110 may be any task undertaking entity. For example, in the embodiment related to workflow X, the task undertaking entity is a staff member. When assigning the task corresponding to process node B, the entity identifier set may be (a1, a2, a3, b1, b2, b3, b4, c1, c2, c3, d1, d2, e1, e2, e3, e4, f1, f2, f3).

[0059] In some embodiments, the task undertaking subject in S110 may also be a subject that has the authority to undertake the target task and is obtained after screening all task undertaking subjects. For example, in the above-mentioned embodiment related to workflow X, the task undertaking subject is a staff member. When allocating the task corresponding to process node B, the subject identification set may be (b1, b2, b3, b4).

[0060] S130: calling a preset inter-system component to obtain status data of each task undertaking subject in the subject identification set from the status system, wherein the task system and the status system are isolated from each other.

[0061] In some embodiments, the status system may be a human resources system, and the status data may be employee leave data. Typically, in an enterprise that prioritizes system or data security, the human resources system and the task system are isolated from each other, meaning that the task system cannot access data from the human resources system.

[0062] In some embodiments, the status data may be a maintenance schedule for a machine or equipment. For example, the status system records the maintenance schedules for three machines, M1, M2, and M3. Machine M1 is scheduled for maintenance from January 1st to January 7th, during which time it cannot process tasks. Typically, maintenance schedules for machines or equipment are managed by the logistics system, which is isolated from the task system. This means that the task system cannot access data from the logistics system.

[0063] The task allocation method provided in the embodiments of this specification sets up inter-system components to enable the task system to obtain data from the status system. Figure 2 The schematic diagram shows an implementation method of obtaining state data from the state system through inter-system components. Among them, the front-end code refers to the user-oriented code. After the user operates the system to initiate the assignment instruction of the target task, the subject identification set of multiple task undertaking subjects is sent to the original system component. The original system component refers to the component used to process the subject identification set in the system before the system is improved by this solution. For example, the function of the original system component can be to process the subject identification set according to the subject identification set. Figure 4 The form shown is presented to the user, and the assignment instruction is processed after the user assigns the target task to the identifier of the target undertaking subject; the function of the original system component can also be to execute an automatic assignment instruction, that is, to assign the target task to the undertaking subject corresponding to an identifier in the subject identifier set. The task assignment method provided in this specification improves the original task assignment system, that is, an inter-system component is set, and the program of the original system component is rewritten. Specifically, the original system component calls the inter-system component, and sets the inter-system component to send a status data acquisition request to the status system. After the status system feeds back the status data, the inter-system component judges the acceptability status of each task undertaking subject in the subject identifier set based on the fed-back status data, and sends the subject identifier and the acceptability status to the original system component, and the original system component feeds back to the front-end code. In some embodiments, Figure 2 The front-end code in can also be other systems or other components.

[0064] S140: Determine the acceptability status of each task accepting subject in the subject identification set according to the status data.

[0065] In some embodiments, the takeover state includes a first state and a second state, wherein the first state is takeoverable within a first predetermined period of time from the current time, and the second state is not takeoverable within the first predetermined period of time from the current time.

[0066] The "first predetermined duration" in this specification may be a pre-set fixed duration, for example, seven days. That is, when assigning tasks, it is possible to see which task undertaking entities are in a state of being able to undertake tasks within the next seven days.

[0067] In some embodiments, the first predetermined duration may also be determined based on the target task to be assigned. For example, the first predetermined duration may be determined as the sum of the target task's estimated processing duration and the difference between the predetermined durations. For example, if the target task's estimated processing duration is 3 days and the difference between the predetermined durations is 1 day (or 0), the first predetermined duration may be 4 days.

[0068] The estimated processing time of the target task can be pre-inputted based on the type of the target task or the characteristic data of the task, or can be predicted by inputting the characteristic data of the target task into a pre-trained prediction model.

[0069] The training method of the prediction model can be: classifying the task data stored in the database according to the type of task; wherein, tasks of the same type have the same type of feature data; the task data includes the feature data of the task and the processing time of the task; training the prediction model for each type of task according to the following method: obtaining multiple task data of a task type; using the processing time in the multiple task data as the output of the prediction model, and using the feature data in the multiple task data as the input of the prediction model, to train the prediction model.

[0070] In some embodiments, the acceptability state may further include a third state, in which part of the time within a first predetermined time period starting from the current time is acceptability and another part of the time is not acceptability. For example, the situation where the start time of the time period during which the task undertaking entity cannot accept the task falls within the first time period but the end time does not fall within the first time period, or the situation where the start time of the time period during which the task undertaking entity cannot accept the task falls outside the first time period but the end time falls within the first time period, both of these situations may be considered the third state. Figure 3A and Figure 3B Two schematic diagrams of the third state are shown.

[0071] It should be noted that the current time in this application can be accurate to the date and month, or to the hour and time of the day, or even to the hour and minute. This description also applies to the following content.

[0072] S150: According to the acceptability status of each task undertaking subject, select at least one task undertaking subject identifier from the subject identifier set as the undertaking node of the target task.

[0073] S150 may select one task undertaking entity as the undertaking node of the target task, or may select identifiers of two or more task undertaking entities as the undertaking node of the target task.

[0074] Using the identifier of the task undertaking subject as the undertaking node of the target task means that the node corresponding to the target task in the workflow is processed by the task undertaking subject corresponding to the identifier.

[0075] After determining the target task's undertaking node, the system can directly assign the target task to the target task's undertaking node determined in S150, or the system can display the target task's undertaking node determined in S150 and its undertaking status to the task assigner, who then assigns the target task to at least one of the target task's undertaking nodes determined in S150. The specific display content can be as follows: Figure 4 shown.

[0076] The above-mentioned task allocation method sets up an inter-system component between the task system and the status system which were originally isolated from each other, so that the task system can obtain the status data of the task undertaking subject from the status system; the above-mentioned task allocation method further determines the acceptance status of each task undertaking subject based on the status data of the task undertaking subject, and then determines the acceptance node of the target task based on the acceptance status of each task undertaking subject, which can avoid the problem that after the target task is assigned to a task undertaking node, the task undertaking node cannot process it in time, restarting the workflow wastes time and human resources, etc., that is, solves the problems of low task completion efficiency and waste of resources.

[0077] In some embodiments, the status data in S130 includes the start time and end time of the time period during which the task cannot be accepted. Figure 5 As shown, S140 may include the following steps:

[0078] S141: If the start time and end time of the time period during which the task undertaking entity cannot undertake tasks are both outside the first time period, determining that the task undertaking entity is in the first state, wherein the first time period is a first predetermined time period from the current time.

[0079] The first state is that the task can be taken over within a first predetermined time period from the current time. Correspondingly, there is a second state, which is that the task cannot be taken over within the first predetermined time period from the current time. Specifically, the second state may be characterized by the start time and end time of the time period during which the task undertaking entity cannot take over the task both being within the first time period.

[0080] Accordingly, if Figure 5 As shown, step S150 may be S151: selecting at least one task undertaking subject in the first state from the subject identification set as the undertaking node of the target task.

[0081] Specifically, the task saturation of each task undertaking subject in the first state in the subject identification set within the first predetermined time period starting from the current time can be obtained; in order of task saturation from low to high, the identification of at least one task undertaking subject is selected as the undertaking node of the target task, that is, the identifications of one or a predetermined number of task undertaking subjects with lower task saturation are selected as the undertaking nodes of the target task.

[0082] Task saturation is used to indicate how busy the task undertaker is. Task saturation can be determined, for example, by obtaining the IDs of each pending task assigned to the task undertaker, along with the estimated processing time for each task. This sum is used to determine the workload, and then the workload is divided by the processing time to determine task saturation. The processing time is the total processing time from the start time to the end time.

[0083] The estimated processing time can be obtained in advance based on the target task type or task feature data, or by inputting the target task feature data into a pre-trained prediction model to predict the result. The prediction model training method can be: classify the task data stored in the database according to task type; wherein tasks of the same type have the same type of feature data; the task data includes the task feature data and the task processing time; and train the prediction model for each type of task according to the following method: obtain multiple task data of the same task type; use the processing time in the multiple task data as the output of the prediction model, and use the feature data in the multiple task data as the input of the prediction model to train the prediction model.

[0084] In some embodiments, the status data in S130 includes the start time and end time of the time period during which the task cannot be accepted. Figure 6 As shown, S140 may include the following steps:

[0085] S142: When the starting time of the time period during which the task undertaking entity cannot undertake the task is within the first time period, and the ending time is not within the first time period, obtain the estimated processing time of the target task; wherein the first time period is the first predetermined time period starting from the current time.

[0086] S143: When the duration from the current time to the second scheduled time is greater than the expected processing time, the task undertaking entity is determined to be in the third state.

[0087] Accordingly, if Figure 6 As shown, S150 includes: S152: selecting at least one task undertaking subject in the third state from the subject identification set as the undertaking node of the target task.

[0088] Specifically, the task saturation of each task undertaking subject in the third state in the subject identification set within the first predetermined time period starting from the current time can be obtained; in order of task saturation from low to high, the identification of at least one task undertaking subject is selected as the undertaking node of the target task, that is, the identifications of one or a predetermined number of task undertaking subjects with lower task saturation are selected as the undertaking nodes of the target task.

[0089] In some embodiments, the status data in S130 includes the start time and end time of the time period during which the task cannot be accepted. Figure 7 As shown, S140 may include the following steps:

[0090] S144: When the starting time of the time period during which the task undertaking entity cannot undertake the task is not within the first time period, but the ending time is within the first time period, obtain the estimated processing time of the target task; wherein the first time period is the first predetermined time period starting from the current time.

[0091] S145: When the estimated processing time of the target task is less than the predetermined time threshold, the task undertaking entity is determined to be in the third state.

[0092] Accordingly, if Figure 7 As shown, S150 includes: S152: selecting at least one task undertaking subject in the third state from the subject identification set as the undertaking node of the target task.

[0093] Specifically, the task saturation of each task undertaking subject in the third state in the subject identification set within the first predetermined time period starting from the current time can be obtained; in order of task saturation from low to high, the identification of at least one task undertaking subject is selected as the undertaking node of the target task, that is, the identifications of one or a predetermined number of task undertaking subjects with lower task saturation are selected as the undertaking nodes of the target task.

[0094] In some embodiments, the above-mentioned “obtaining the estimated processing time of the target task” may include: obtaining characteristic data of the target task; inputting the characteristic data of the target task into a pre-trained prediction model to predict the estimated processing time of the target task.

[0095] The training method of the prediction model can be: classifying the task data stored in the database according to the type of task; wherein, tasks of the same type have the same type of feature data; the task data includes the feature data of the task and the processing time of the task; training the prediction model for each type of task according to the following method: obtaining multiple task data of a task type; using the processing time in the multiple task data as the output of the prediction model, and using the feature data in the multiple task data as the input of the prediction model, to train the prediction model.

[0096] In some embodiments, the status data in S130 includes the start time and end time of the time period during which the task cannot be accepted. Figure 8 As shown, S140 may include the following steps:

[0097] S146: When the starting time of the time period during which the task undertaking entity cannot undertake the task is not within the first time period, but the ending time is within the first time period, obtain the urgency of the target task; wherein the first time period is the first predetermined duration from the current time.

[0098] The urgency of the target task can be determined based on the expected completion time. For example, if it is expected to be completed within 1 day, the urgency is 1; if it is expected to be completed within a week, the urgency is 7. The smaller the number, the higher the urgency.

[0099] S147: When the urgency of the target task is lower than a predetermined threshold, the task undertaking entity is determined to be in the third state.

[0100] Accordingly, if Figure 8 As shown, S150 includes: S152: selecting at least one task undertaking subject in the third state from the subject identification set as the undertaking node of the target task.

[0101] For example, when the urgency of the target task is 7 (ie, not urgent) and the remaining time of the employee on leave is 1 day, the employee on leave can be used as the target employee for target task assignment.

[0102] In some embodiments, Figure 5 、 Figure 6 、 Figure 7 Based on the above technical solution, before step S152, the task saturation of each task undertaking subject in the first state in the subject identification set within a first predetermined time period from the current time can also be obtained. S152 is only executed when the task saturation of each task undertaking subject is greater than a predetermined saturation threshold.

[0103] This specification provides a task allocation device that can be used to implement the task allocation method provided in this specification. Figure 9A As shown, the task allocation device includes a receiving unit 10 , an acquiring unit 20 , a calling unit 30 , a determining unit 40 and a selecting unit 50 .

[0104] The receiving unit 10 is used for the task system to receive the assignment instruction of the target task.

[0105] The acquisition unit 20 is used to acquire a set of subject identifications of the task undertaking subject in response to the allocation instruction.

[0106] The calling unit 30 is used to call a preset inter-system component to obtain the status data of each task undertaking subject in the subject identification set from the status system, wherein the task system and the status system are isolated from each other.

[0107] The determining unit 40 is used to determine the acceptability status of each task accepting subject in the subject identification set according to the status data.

[0108] The selection unit 50 is used to select at least one task undertaking subject identifier from the subject identifier set as the undertaking node of the target task according to the undertaking status of each task undertaking subject.

[0109] In some embodiments, as Figure 9B As shown, the acceptability status includes: a first status and a second status, wherein the first status indicates that the task can be accepted within a first predetermined time period from the current time, and the second status indicates that the task cannot be accepted within a first predetermined time period from the current time. Accordingly, the selection unit 50 includes: a first selection subunit 51, which is used to select the identifier of at least one task acceptance subject in the first status from the subject identifier set as the acceptance node of the target task.

[0110] In some embodiments, as Figure 9B As shown, the first selection subunit 51 includes a first acquisition subunit 52 and a second selection subunit 53 .

[0111] The first acquisition subunit 52 is used to obtain the task saturation of each task undertaking entity in the first state in the entity identifier set within a first predetermined time period from the current time. The second selection subunit 53 is used to select the identifier of at least one task undertaking entity as the undertaking node of the target task in order of task saturation from low to high.

[0112] In some embodiments, as Figure 9C As shown, the status data includes the start time and end time of the time period in which the task cannot be undertaken. Accordingly, the determining unit 40 includes a second obtaining subunit 41 and a first determining subunit 42.

[0113] The second acquisition subunit 41 is configured to acquire the estimated processing time of the target task if the start time of the time period during which the task undertaking entity cannot undertake tasks falls within a first time period, but the end time does not fall within the first time period; wherein the first time period is a first predetermined time period from the current time. The first determination subunit 42 is configured to determine that the task undertaking entity is in the third state if the time period from the current time to the second predetermined time period exceeds the estimated processing time.

[0114] Correspondingly, the selection unit 50 includes: a third selection subunit 54, which is used to select the identifier of at least one task undertaking subject in the third state from the subject identifier set as the undertaking node of the target task.

[0115] In some embodiments, as Figure 9CAs shown, the status data includes the start time and end time of the time period in which the task cannot be undertaken. Accordingly, the determining unit 40 includes a third obtaining subunit 43 and a second determining subunit 44.

[0116] The third acquisition subunit 43 is configured to acquire the estimated processing duration of the target task if the start time of the time period during which the task undertaking entity cannot undertake tasks is not within the first time period, but the end time is within the first time period; wherein the first time period is a first predetermined time period from the current time. The second determination subunit 44 is configured to determine that the task undertaking entity is in the third state if the estimated processing duration of the target task is less than a predetermined time threshold.

[0117] Correspondingly, the selection unit 50 includes: a third selection subunit 54, which is used to select the identifier of at least one task undertaking subject in the third state from the subject identifier set as the undertaking node of the target task.

[0118] In some embodiments, the second acquisition subunit 41 or the third acquisition subunit 43 includes a fourth acquisition subunit 431 and a prediction subunit 432 .

[0119] The fourth acquisition subunit 431 is used to acquire characteristic data of the target task. The prediction subunit 432 is used to input the characteristic data of the target task into a pre-trained prediction model to predict the estimated processing time of the target task.

[0120] In some embodiments, a classification unit 60 and a training unit 70 are further included.

[0121] The classification unit 60 is used to classify the task data stored in the database according to task type. Tasks of the same type have the same type of feature data. The task data includes the feature data and the task processing time. The training unit 70 is used to train a prediction model for each type of task by obtaining multiple task data of the same task type; using the processing time in the multiple task data as the output of the prediction model and the feature data in the multiple task data as the input of the prediction model.

[0122] In some embodiments, as Figure 9C As shown, the status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, the determination unit 40 includes a fifth acquisition subunit 45 and a third determination subunit 46.

[0123] The fifth obtaining subunit 45 is configured to obtain the urgency of the target task if the start time of the time period during which the task undertaking entity cannot undertake tasks is not within the first time period, but the end time is within the first time period; wherein the first time period is a first predetermined duration from the current time. The third determining subunit 46 is configured to determine that the task undertaking entity is in the third state if the urgency of the target task is below a predetermined threshold.

[0124] Correspondingly, the selection unit 50 includes: a third selection subunit 54, which is used to select the identifier of at least one task undertaking subject in the third state from the subject identifier set as the undertaking node of the target task.

[0125] In some embodiments, it further includes: a sixth obtaining subunit 47 for obtaining the task saturation of each task undertaking subject in the first state in the subject identification set within a first predetermined time period from the current time.

[0126] When the task saturation of each task undertaking subject is greater than the predetermined saturation threshold, the third selection subunit 54 selects the identifier of at least one task undertaking subject in the third state from the subject identifier set as the undertaking node of the target task.

[0127] The description and beneficial effects of the above-mentioned task allocation device can be found in the description and beneficial effects of the method part, which will not be repeated here.

[0128] The embodiment of the present invention further provides an electronic device, such as Figure 10 As shown, the electronic device may include a processor 1001 and a memory 1002, wherein the processor 1001 and the memory 1002 may be connected via a bus or other means. Figure 10 The bus connection is taken as an example.

[0129] The processor 1001 may be a central processing unit (CPU). The processor 1001 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0130] The memory 1002 is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions / modules corresponding to the task allocation method in the embodiment of the present invention (for example, Figure 9A The processor 1001 executes various functional applications and data classifications of the processor by running the non-transitory software programs, instructions, and modules stored in the memory 1002, thereby implementing the task allocation method in the above method embodiment.

[0131] The memory 1002 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created by the processor 1001, etc. In addition, the memory 1002 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 1002 may optionally include a memory remotely located relative to the processor 1001, and these remote memories may be connected to the processor 1001 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0132] The one or more modules are stored in the memory 1002 and when executed by the processor 1001, perform the following steps: Figure 1 、 Figures 4 to 8 The task allocation method in the illustrated embodiment.

[0133] For details of the above electronic equipment, please refer to Figure 1 、 Figures 4 to 8 The relevant descriptions and effects in the corresponding embodiments have been understood and will not be repeated here.

[0134] This specification provides a computer storage medium that stores computer program instructions. When the computer program instructions are executed by a processor, Figure 1 、 Figures 4 to 8 Steps of the method shown.

[0135] This specification provides a computer program product, which includes a computer program, which, when executed by a processor, implements Figure 1 、 Figures 4 to 8 Steps of the method shown.

[0136] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD). The storage medium can also include a combination of the above-mentioned types of memory.

[0137] In the 1990s, technological improvements could be clearly distinguished as either hardware improvements (for example, improvements to circuit structures such as diodes, transistors, and switches) or software improvements (improvements to process flows). However, with the advancement of technology, many process flow improvements today can now be considered direct improvements to hardware circuit structures. Designers almost always obtain the corresponding hardware circuit structure by programming the improved process flow into the hardware circuit. Therefore, it cannot be said that a process flow improvement cannot be implemented using hardware modules. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is an integrated circuit whose logical function is determined by user programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to hire a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this type of programming is mostly performed using "logic compiler" software. This is similar to the software compiler used when developing programs. Before compilation, the original code must also be written in a specific programming language, called a hardware description language (HDL). There is not just one HDL, but many, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog2. Those skilled in the art will also understand that by simply programming the method flow in one of these hardware description languages ​​and then programming it into an integrated circuit, a hardware circuit that implements the logic method flow can be easily obtained.

[0138] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0139] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions.

[0140] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0141] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that the present application can be implemented by means of software plus the necessary general hardware platform. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute certain parts of the methods of each embodiment of the present application.

[0142] The present application can be used in a wide variety of general-purpose or specialized computer system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above.

[0143] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0144] Although the present application has been described through embodiments, those skilled in the art will appreciate that there are many modifications and variations to the present application without departing from the spirit of the present application. It is intended that the appended claims include these modifications and variations without departing from the spirit of the present application.

Claims

1. A task allocation method, characterized in that: include: The task system receives the assignment instruction of the target task; In response to the assignment instruction, obtaining a subject identification set of a task undertaking subject; Calling a pre-set inter-system component to obtain status data of each task undertaking subject in the subject identification set from a status system, wherein the task system and the status system are isolated from each other; Determining the acceptability status of each task accepting subject in the subject identification set according to the status data; According to the acceptability status of each task undertaking subject, selecting at least one task undertaking subject identifier from the subject identifier set as the undertaking node of the target task; The method further comprises: The status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, determining the acceptability status of each task undertaking subject in the subject identification set based on the status data includes: When the start time of the time period during which the task undertaking entity cannot undertake the task is within the first time period, and the end time is not within the first time period, obtaining the estimated processing time of the target task; wherein the first time period is the first predetermined time period starting from the current time; Determine whether the duration from the current time to the start time is greater than the estimated processing time; If the time from the current time to the second scheduled time is longer than the estimated processing time, determining that the task undertaking entity is in the third state; Accordingly, according to the acceptability status of each task accepting subject, at least one task accepting subject is selected from the subject identification set as the accepting node of the target task, including: Selecting an identifier of at least one task undertaking entity in the third state from the entity identifier set as the undertaking node of the target task; Alternatively, the method further comprises: The status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, determining the acceptability status of each task undertaking subject in the subject identification set based on the status data includes: When the starting time of the time period during which the task undertaking entity cannot undertake the task is not within the first time period, but the ending time is within the first time period, obtaining the estimated processing time of the target task; wherein the first time period is the first predetermined time period starting from the current time; When the estimated processing time of the target task is less than the predetermined time threshold, determining that the task undertaking entity is in the third state; Accordingly, according to the acceptability status of each task accepting subject, at least one task accepting subject is selected from the subject identification set as the accepting node of the target task, including: Selecting an identifier of at least one task undertaking entity in the third state from the entity identifier set as the undertaking node of the target task; Alternatively, the method further comprises: The status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, determining the acceptability status of each task undertaking subject in the subject identification set based on the status data includes: When the starting time of the time period during which the task undertaking entity cannot undertake the task is not within the first time period, but the ending time is within the first time period, obtaining the urgency of the target task; wherein the first time period is the first predetermined time period from the current time; When the urgency of the target task is lower than the predetermined threshold, the task undertaking entity is determined to be in the third state; Accordingly, according to the acceptability status of each task accepting subject, at least one task accepting subject is selected from the subject identification set as the accepting node of the target task, including: An identifier of at least one task undertaking entity in the third state is selected from the entity identifier set as the undertaking node of the target task.

2. The method according to claim 1, characterized in that The acceptability status includes: a first status and a second status, wherein the first status indicates that the task can be accepted within a first predetermined time period from the current time, and the second status indicates that the task cannot be accepted within the first predetermined time period from the current time; accordingly, according to the acceptability status of each task acceptance subject, at least one task acceptance subject is selected from the subject identifier set as the acceptance node of the target task, including: An identifier of at least one task undertaking entity in the first state is selected from the entity identifier set as a undertaking node of the target task.

3. The method according to claim 2, characterized in that Selecting at least one task undertaking subject in the first state from the subject identification set as the undertaking node of the target task includes: Obtaining the task saturation of each task undertaking subject in the first state in the subject identification set within a first predetermined time period starting from the current time; In order of task saturation from low to high, an identifier of at least one task undertaking entity is selected as an undertaking node of the target task.

4. The method according to claim 1, wherein Get the estimated processing time of the target task, including: Obtain characteristic data of the target task; The characteristic data of the target task is input into the pre-trained prediction model to predict the estimated processing time of the target task.

5. The method according to claim 4, characterized in that Before inputting the target task's feature data into the pre-trained prediction model and predicting the expected processing time for the target task, the following steps are also required: Classifying the task data stored in the database according to the type of task; wherein tasks of the same type have the same type of characteristic data; the task data includes the characteristic data of the task and the processing time of the task; Train a prediction model for each type of task as follows: Get multiple task data of a task type; The prediction model is trained by using the processing durations in the plurality of task data as outputs of the prediction model and using the feature data in the plurality of task data as inputs of the prediction model.

6. The method according to claim 1, characterized in that Before selecting at least one task undertaking subject in the third state from the subject identifier set as the undertaking node of the target task, the method further includes: Obtaining the task saturation of each task undertaking subject in the first state in the subject identification set within a first predetermined time period starting from the current time; When the task saturation of each task undertaking subject is greater than a predetermined saturation threshold, the step of selecting an identifier of at least one task undertaking subject in the third state from the subject identifier set as the undertaking node of the target task is executed.

7. A task allocation device, characterized in that: include: A receiving unit, used for the task system to receive the assignment instruction of the target task; an acquiring unit, configured to acquire a set of subject identifiers of the subject undertaking the task in response to the assignment instruction; a calling unit, configured to call a pre-set inter-system component to obtain status data of each task undertaking subject in the subject identification set from a status system, wherein the task system and the status system are isolated from each other; a determination unit, configured to determine, based on the status data, the acceptability status of each task accepting subject in the subject identification set; a selection unit, configured to select, from the subject identifier set, an identifier of at least one task undertaking subject as a node for undertaking the target task according to the availability of each task undertaking subject; The device further comprises: The status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, the determining unit includes: The second acquisition subunit is configured to acquire an estimated processing duration of the target task when the start time of the time period during which the task undertaking entity cannot undertake the task is within a first time period and the end time is not within the first time period; wherein the first time period is a first predetermined duration starting from the current time; The first determining subunit is configured to determine that the task undertaking entity is in the third state when the time from the current time to the second predetermined time is longer than the estimated processing time; Accordingly, the selection unit includes: A third selection subunit is configured to select an identifier of at least one task undertaking entity in the third state from the entity identifier set as an undertaking node for the target task; Alternatively, the device is further used for: The status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, determining the acceptability status of each task undertaking subject in the subject identification set based on the status data includes: When the starting time of the time period during which the task undertaking entity cannot undertake the task is not within the first time period, but the ending time is within the first time period, obtaining the estimated processing time of the target task; wherein the first time period is the first predetermined time period starting from the current time; When the estimated processing time of the target task is less than the predetermined time threshold, determining that the task undertaking entity is in the third state; Accordingly, according to the acceptability status of each task accepting subject, at least one task accepting subject is selected from the subject identification set as the accepting node of the target task, including: Selecting an identifier of at least one task undertaking entity in the third state from the entity identifier set as the undertaking node of the target task; Alternatively, the device is further used for: The status data includes the start time and end time of the time period in which the task cannot be undertaken; accordingly, determining the acceptability status of each task undertaking subject in the subject identification set based on the status data includes: When the starting time of the time period during which the task undertaking entity cannot undertake the task is not within the first time period, but the ending time is within the first time period, obtaining the urgency of the target task; wherein the first time period is the first predetermined time period from the current time; When the urgency of the target task is lower than the predetermined threshold, the task undertaking entity is determined to be in the third state; Accordingly, according to the acceptability status of each task accepting subject, at least one task accepting subject is selected from the subject identification set as the accepting node of the target task, including: An identifier of at least one task undertaking entity in the third state is selected from the entity identifier set as the undertaking node of the target task.

8. The device according to claim 7, characterized in that The takeover status includes: a first status and a second status, wherein the first status indicates that the call can be taken over within a first predetermined time period from the current time, and the second status indicates that the call cannot be taken over within the first predetermined time period from the current time; accordingly, the selection unit includes: The first selection subunit is configured to select an identifier of at least one task undertaking entity in the first state from the entity identifier set as a undertaking node for the target task.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the processor and the memory are communicatively connected to each other, the memory stores computer instructions, and the processor implements the steps of the method according to any one of claims 1 to 6 by executing the computer instructions.

10. A computer storage medium, characterized in that The computer storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

11. A computer program product, characterized in that The invention comprises a computer program, which implements the steps of the method according to any one of claims 1 to 6 when the computer program is executed by a processor.

Images