CN112150023A - Task allocation method, device and storage medium - Google Patents
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Abstract
The invention relates to the technical field of computers, and discloses a task allocation method, a device and a storage medium, wherein the method comprises the steps of receiving a work task issued by a user side; acquiring a task abstract of a work task; extracting task keywords from the task abstract; generating a user representation of each user in the user list based on the current task state data of each user in the user list and the historical task completion data of each user in the user list; matching the task keywords with the user portrait of each user in the user list to determine a target portrait matched with the task keywords; the work task is assigned to a user corresponding to the target representation. The task allocation method, the device and the storage medium disclosed by the invention can complete the allocation of the work tasks very conveniently and can allocate the most suitable processing user to the work tasks.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a task allocation method, a task allocation device and a storage medium.
Background
In enterprise management work, the reasonable distribution of work tasks is the guarantee that the work tasks can be completed on time and according to quality.
At present, in the process of distributing work tasks, enterprise managers often manually distribute the work tasks based on personal experience of the enterprise managers, and the distribution of the work tasks needs to be reasonable in fitting, and needs a large amount of statistical work as support, so that when the enterprise managers manually distribute the work tasks, the distributed work tasks are easy to be distributed unreasonably.
Therefore, how to provide an effective solution to facilitate the reasonable distribution of work tasks has become an urgent problem in the prior art.
Disclosure of Invention
In order to solve the problem that the work tasks are easy to be distributed unreasonably in the prior art, the invention aims to provide a task distribution method, a task distribution device and a storage medium to achieve reasonable distribution of the work tasks.
In a first aspect, the present invention provides a task allocation method, including:
receiving a work task issued by a user side;
acquiring a task abstract of the work task;
extracting task keywords from the task abstract;
generating a user representation of each user in a user list based on current task state data of each user in the user list and historical task completion data of each user in the user list;
matching the task keywords with the user portrait of each user in the user list, and determining a target portrait matched with the task keywords;
and distributing the work task to a user corresponding to the target image.
In one possible design, the generating a user representation of each user in the user list based on current task state data for each user in the user list and historical task completion data for each user in the user list includes:
generating a user representation of each user in the user list based on a task list being processed by each user in the user list, a task progress of each task in the task list, a historical task processing performance of each user in the user list, and a historical task processing quality of each user in the user list.
In one possible design, the extracting task keywords from the task abstract includes:
and extracting task keywords from the task abstract based on a natural language processing algorithm.
In one possible design, the obtaining a task summary of the work task includes:
and acquiring a task abstract of the work task through a Chinese word segmentation algorithm.
In one possible design, the matching the task keyword with the user representation of each user in the user list to determine a target representation matching the task keyword includes:
matching the task keywords with the user images of each user in the user list, and determining a plurality of target images with the highest matching degree with the task keywords;
the allocating the work task to the user corresponding to the target image comprises:
respectively giving task orders of the work tasks to a plurality of users corresponding to the target images one by one;
and when receiving an order taking request of at least one user in the plurality of users, distributing the work task to the user which initiates the order taking request firstly in the plurality of users.
In one possible design, the matching the task keyword with the user representation of each user in the user list to determine a target representation matching the task keyword includes:
matching the task keywords with the user images of each user in the user list, and determining a plurality of target images with the highest matching degree with the task keywords;
the allocating the work task to the user corresponding to the target image comprises:
responding to the allocation operation of the user side, and allocating the work task to a user corresponding to a target image indicated by the allocation operation.
In a second aspect, the present invention provides a task assigning apparatus, including:
the receiving unit is used for receiving the work tasks issued by the user side;
the acquisition unit is used for acquiring a task abstract of the work task;
the extraction unit is used for extracting task keywords from the task abstract;
a generating unit, configured to generate a user representation of each user in a user list based on current task state data of each user in the user list and historical task completion data of each user in the user list;
the matching unit is used for matching the task keywords with the user portrait of each user in the user list and determining a target portrait matched with the task keywords;
and the distribution unit is used for distributing the work task to the user corresponding to the target image.
In one possible design, the generating unit, when configured to generate the user representation for each user in the user list based on the current task state data for each user in the user list and the historical task completion data for each user in the user list, is specifically configured to:
generating a user representation of each user in the user list based on a task list being processed by each user in the user list, a task progress of each task in the task list, a historical task processing performance of each user in the user list, and a historical task processing quality of each user in the user list.
In a third aspect, the present invention provides another task allocation apparatus, including a memory, a processor and a transceiver, which are sequentially connected in communication, where the memory is used for storing a computer program, the transceiver is used for sending and receiving a message, and the processor is used for reading the computer program and executing the task allocation method according to the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon instructions which, when run on a computer, perform the task allocation method of the first aspect.
In a fifth aspect, the present invention provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform a method of task allocation as described in the first aspect.
The task allocation method, the device and the storage medium provided by the invention at least have the following beneficial effects:
the task allocation method, the device and the storage medium can generate the user portrait of each user according to the current task state data and the historical task completion data of each user, extract the task keywords from the task abstract to match with the target portrait matched with the task keywords, and allocate the work task to the user corresponding to the target portrait. Therefore, the users most suitable for processing the work task can be matched for the work task according to the user portrait of each user, so that the reasonable distribution of the task is realized, and effective guarantee is provided for the completion of the work task according to time and quality.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of an application environment of a task allocation method, a task allocation device, and a storage medium according to the present invention.
FIG. 2 is a flow chart of a task assignment method provided by the present invention.
Fig. 3 is a schematic structural diagram of a task allocation device provided by the present invention.
Fig. 4 is a schematic structural diagram of another task allocation device provided by the present invention.
Detailed Description
The invention is further described with reference to the following figures and specific embodiments. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. Specific structural and functional details disclosed herein are merely illustrative of example embodiments of the invention. This invention may, however, be embodied in many alternate forms and should not be construed as limited to the embodiments set forth herein.
It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments of the present invention.
It should be understood that, for the term "and/or" as may appear herein, it is merely an associative relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, B exists alone, and A and B exist at the same time; for the term "/and" as may appear herein, which describes another associative object relationship, it means that two relationships may exist, e.g., a/and B, may mean: a exists independently, and A and B exist independently; in addition, for the character "/" that may appear herein, it generally means that the former and latter associated objects are in an "or" relationship.
It will be understood that when an element is referred to herein as being "connected," "connected," or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may be present. Conversely, if a unit is referred to herein as being "directly connected" or "directly coupled" to another unit, it is intended that no intervening units are present. In addition, other words used to describe the relationship between elements should be interpreted in a similar manner (e.g., "between … …" versus "directly between … …", "adjacent" versus "directly adjacent", etc.).
It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments of the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, numbers, steps, operations, elements, components, and/or groups thereof.
It should also be noted that, in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed substantially concurrently, or the figures may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
It should be understood that specific details are provided in the following description to facilitate a thorough understanding of example embodiments. However, it will be understood by those of ordinary skill in the art that the example embodiments may be practiced without these specific details. For example, systems may be shown in block diagrams in order not to obscure the examples in unnecessary detail. In other instances, well-known processes, structures and techniques may be shown without unnecessary detail in order to avoid obscuring example embodiments.
Examples
In order to implement reasonable allocation of work tasks, embodiments of the present application provide a task allocation method, a task allocation device, and a storage medium, where the task allocation method, the task allocation device, and the storage medium can match a user most suitable for processing the work task for the work task, thereby implementing reasonable allocation of tasks.
First, in order to more intuitively understand the scheme provided by the embodiment of the present application, a system architecture of the task allocation scheme provided by the embodiment of the present application is described below with reference to fig. 1.
Fig. 1 is a schematic application environment diagram of a task allocation method, a task allocation apparatus, and a storage medium according to one or more embodiments of the present application. As shown in fig. 1, one or more user terminals are communicatively connected to a server terminal through a network so as to distribute work tasks to the server terminal. The user side may be a personal computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), or the like for issuing a work task, and the server side may be a server for distributing the issued work task.
The task allocation method provided by the embodiment of the present application will be described in detail below.
The task allocation method provided by the embodiment of the application can be applied to a server. For convenience of description, the embodiments of the present application are described with a server as an execution subject unless otherwise specified.
It is to be understood that the subject matter described herein is not to be construed as limiting the embodiments of the disclosure.
Specifically, the flow of the task allocation method is shown in fig. 2, and may include the following steps:
step S201, receiving a work task issued by a user side.
The number of the work tasks issued by the user side may be one or more, the content of the work tasks includes task names, specific descriptions of the tasks, and the like, and the embodiment of the present application is not particularly limited.
And S202, acquiring a task abstract of the work task.
The task abstract refers to the summary of the content of the work task, and in the embodiment of the application, the task abstract of the work task can be obtained through a Chinese word segmentation algorithm.
And S203, extracting task keywords from the task abstract.
In the embodiment of the present application, the task keyword may be extracted from the task summary based on a Natural Language Processing (NLP) algorithm.
And S204, generating a user portrait of each user in the user list based on the current task state data of each user in the user list and the historical task completion data of each user in the user list.
The user's current task state data may include, but is not limited to, a list of tasks the user is processing, a task progress for each task in the task list, and the like. The historical task completion data of the user may include, but is not limited to, historical task processing performance, historical task processing quality, etc. of the user.
The task list being processed by the user may be a task type, a task name, a task number, and the like of the task being processed by the user, and the task progress of the task may be a completion degree of the task, a remaining completion time of the task, and the like. The historical task processing efficiency of the user can be the on-time completion rate or completion time of the historical task of the user, and the historical task processing quality can be the processing grading value or grading level of the historical task.
In generating the user profile for each user, a user profile for each user in the user list may be generated based on a task list being processed by each user in the user list, a task progress of each task in the task list, a historical task processing performance for each user in the user list, and a historical task processing quality for each user in the user list. The content of each user portrait comprises a task list which is processed by the corresponding user, the task progress of each task in the task list, the historical task processing efficiency of the user and the historical task processing quality of the user.
The task list being processed by the user is assumed to comprise the task type and the task number of the task being processed by the user, the task progress of the task comprises the remaining completion time of the task, the historical task processing efficiency of the user comprises the on-time completion rate of the historical task of the user, and the historical task processing quality of the user comprises the processing grading value of the historical task of the user. The generated user profile content includes the task type, number of tasks, remaining completion time of the tasks, on-time completion rate of the user's historical tasks, and processing credit value of the user's historical tasks, etc. for which the user is processing tasks.
And S205, matching the task keywords with the user portrait of each user in the user list to determine a target portrait matched with the task keywords.
The target images can be one or more, and when matching is carried out, the target images can be matched with the user images of each user in the user list according to the task keywords, and one or more target images with the highest matching degree with the task keywords are determined.
In the matching process, weighting operation can be carried out according to the similarity between the task type of the task being processed by the user and the task keywords, the number of the tasks, the residual completion time of the tasks, the on-time completion rate of the historical tasks of the user and the processing score value of the historical tasks of the user, so that the matching degree between the task keywords and each user portrait is obtained.
The higher the similarity between the task type of the task being processed by the user and the task keyword, the larger the corresponding weight value. The larger the number of tasks, the smaller the corresponding weight value. The longer the task residual completion time is, the smaller the corresponding weight value is. The higher the on-time completion rate of the user historical task, the higher the corresponding weight. The higher the processing score value of the user's historical task, the greater the corresponding weight. The user corresponding to the target portrait matched in this way is a user who is processing a task similar to the work task, the user has enough time to process the task at present, and the task completion efficiency and the task completion quality of the user are good. I.e. the user to which the target image corresponds is the one or more users that are most suitable for handling the issued work task.
And S206, distributing the work task to a user corresponding to the target portrait.
In this embodiment, the target representation may be one or more. If there is one target portrait, the work task can be directly assigned to the user corresponding to the target portrait.
When a plurality of target images are displayed, the following method is used for distributing the work task.
The first method is as follows: first, a task order of a job task is assigned to a plurality of users corresponding to a plurality of target images one by one. Then, when receiving the order taking request of at least one user in the plurality of users, distributing the work task to the user which initiates the order taking request firstly in the plurality of users.
In such a way, a plurality of users suitable for processing the work tasks can be determined, the work tasks are distributed to the users willing to receive orders, and the reasonable distribution of the tasks is further ensured by considering the own will of the users while the tasks are distributed to the users suitable for processing.
The second method comprises the following steps: and responding to the allocation operation of the user side, and allocating the work task to the user corresponding to the target image indicated by the allocation operation.
Therefore, a plurality of users suitable for processing the work tasks can be determined, the enterprise manager at the user side distributes the work tasks to one of the users suitable for processing the work tasks according to the actual situation, and reasonable distribution of the tasks is further guaranteed.
Therefore, by the task allocation method described in the foregoing steps S201 to S206, a user portrait of each user can be generated according to the current task state data and the historical task completion data of each user, a target portrait matched with the task keyword is extracted from the task abstract and matched with the task keyword, and the work task is allocated to the user corresponding to the target portrait. Therefore, the users most suitable for processing the work task can be matched for the work task according to the user portrait of each user, so that the reasonable distribution of the task is realized, and effective guarantee is provided for the completion of the work task according to time and quality. In addition, when a plurality of target images are determined, the work tasks can be distributed to the users corresponding to one target image according to the order receiving requests of the users or the distribution operation of the enterprise managers, the users are ensured to process the distributed work tasks most appropriately, meanwhile, the work tasks are distributed according to the self intentions of the users or the work arrangement of the enterprise managers, and the reasonable distribution of the tasks is further ensured.
In a second aspect, an embodiment of the present application provides a task allocation apparatus, where the task allocation apparatus is applicable to a server, please refer to fig. 3, and the task allocation apparatus includes:
the receiving unit is used for receiving the work tasks issued by the user side;
the acquisition unit is used for acquiring a task abstract of the work task;
the extraction unit is used for extracting task keywords from the task abstract;
a generating unit, configured to generate a user representation of each user in a user list based on current task state data of each user in the user list and historical task completion data of each user in the user list;
the matching unit is used for matching the task keywords with the user portrait of each user in the user list and determining a target portrait matched with the task keywords;
and the distribution unit is used for distributing the work task to the user corresponding to the target image.
In one possible design, the generating unit, when configured to generate the user representation for each user in the user list based on the current task state data for each user in the user list and the historical task completion data for each user in the user list, is specifically configured to:
generating a user representation of each user in the user list based on a task list being processed by each user in the user list, a task progress of each task in the task list, a historical task processing performance of each user in the user list, and a historical task processing quality of each user in the user list.
In one possible design, the matching unit is specifically configured to, when the matching unit is configured to match the task keyword with the user image of each user in the user list and determine a target image matching the task keyword:
matching the task keywords with the user images of each user in the user list, and determining a plurality of target images with the highest matching degree with the task keywords;
when the allocating unit is configured to allocate the work task to the user corresponding to the target icon, the allocating unit is specifically configured to:
respectively giving task orders of the work tasks to a plurality of users corresponding to the target images one by one;
and when receiving an order taking request of at least one user in the plurality of users, distributing the work task to the user which initiates the order taking request firstly in the plurality of users.
In one possible design, the matching unit is specifically configured to, when the matching unit is configured to match the task keyword with the user image of each user in the user list and determine a target image matching the task keyword:
matching the task keywords with the user images of each user in the user list, and determining a plurality of target images with the highest matching degree with the task keywords;
when the allocating unit is configured to allocate the work task to the user corresponding to the target icon, the allocating unit is specifically configured to:
responding to the allocation operation of the user side, and allocating the work task to a user corresponding to a target image indicated by the allocation operation.
For the working process, the working details, and the technical effects of the apparatus provided in the second aspect of this embodiment, reference may be made to the first aspect of this embodiment, which is not described herein again.
As shown in fig. 4, a third aspect of the embodiments of the present application provides a task allocation apparatus, including a memory, a processor, and a transceiver, which are sequentially connected in a communication manner, where the memory is used to store a computer program, the transceiver is used to transmit and receive a message, and the processor is used to read the computer program and execute the task allocation method according to the first aspect of the embodiments.
By way of specific example, the Memory may include, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Flash Memory (Flash Memory), a first-in-first-out Memory (FIFO), a first-in-last-out Memory (FILO), and/or the like; the processor may not be limited to a processor adopting an architecture processor such as a model STM32F105 series microprocessor, an arm (advanced RISC machines), an X86, or a processor of an integrated NPU (neutral-network processing unit); the transceiver may be, but is not limited to, a WiFi (wireless fidelity) wireless transceiver, a bluetooth wireless transceiver, a General Packet Radio Service (GPRS) wireless transceiver, a ZigBee protocol (ieee 802.15.4 standard-based low power local area network protocol), a 3G transceiver, a 4G transceiver, and/or a 5G transceiver, etc.
For the working process, the working details, and the technical effects of the apparatus provided in the third aspect of this embodiment, reference may be made to the first aspect of the embodiment, which is not described herein again.
A fourth aspect of the present embodiment provides a computer-readable storage medium storing instructions including the task allocation method according to the first aspect of the present embodiment, that is, the computer-readable storage medium has instructions stored thereon, and when the instructions are executed on a computer, the task allocation method according to the first aspect is performed. The computer-readable storage medium refers to a carrier for storing data, and may include, but is not limited to, floppy disks, optical disks, hard disks, flash memories, flash disks and/or Memory sticks (Memory sticks), etc., and the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
For a working process, working details, and technical effects of the computer-readable storage medium provided in the fourth aspect of this embodiment, reference may be made to the first aspect of the embodiment, which is not described herein again.
A fifth aspect of the present embodiments provides a computer program product comprising instructions which, when run on a computer, wherein the computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus, cause the computer to perform the method of task allocation according to the first aspect of the embodiments.
The embodiments described above are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a repository code combining means to execute the methods according to the embodiments or parts of the embodiments.
The invention is not limited to the above alternative embodiments, and any other various forms of products can be obtained by anyone in the light of the present invention, but any changes in shape or structure thereof, which fall within the scope of the present invention as defined in the claims, fall within the scope of the present invention.
Claims (10)
1. A task allocation method, comprising:
receiving a work task issued by a user side;
acquiring a task abstract of the work task;
extracting task keywords from the task abstract;
generating a user representation of each user in a user list based on current task state data of each user in the user list and historical task completion data of each user in the user list;
matching the task keywords with the user portrait of each user in the user list, and determining a target portrait matched with the task keywords;
and distributing the work task to a user corresponding to the target image.
2. The method of claim 1, wherein generating a user representation of each user in the user list based on current task state data for each user in the user list and historical task completion data for each user in the user list comprises:
generating a user representation of each user in the user list based on a task list being processed by each user in the user list, a task progress of each task in the task list, a historical task processing performance of each user in the user list, and a historical task processing quality of each user in the user list.
3. The method of claim 1, wherein said extracting task keywords from said task summary comprises:
and extracting task keywords from the task abstract based on a natural language processing algorithm.
4. The method of claim 1, wherein said obtaining a task summary of the work task comprises:
and acquiring a task abstract of the work task through a Chinese word segmentation algorithm.
5. The method of claim 1, wherein matching the task key to a user representation for each user in the user list to determine a target representation that matches the task key comprises:
matching the task keywords with the user images of each user in the user list, and determining a plurality of target images with the highest matching degree with the task keywords;
the allocating the work task to the user corresponding to the target image comprises:
respectively giving task orders of the work tasks to a plurality of users corresponding to the target images one by one;
and when receiving an order taking request of at least one user in the plurality of users, distributing the work task to the user which initiates the order taking request firstly in the plurality of users.
6. The method of claim 1, wherein matching the task key to a user representation for each user in the user list to determine a target representation that matches the task key comprises:
matching the task keywords with the user images of each user in the user list, and determining a plurality of target images with the highest matching degree with the task keywords;
the allocating the work task to the user corresponding to the target image comprises:
responding to the allocation operation of the user side, and allocating the work task to a user corresponding to a target image indicated by the allocation operation.
7. A task assigning apparatus, comprising:
the receiving unit is used for receiving the work tasks issued by the user side;
the acquisition unit is used for acquiring a task abstract of the work task;
the extraction unit is used for extracting task keywords from the task abstract;
a generating unit, configured to generate a user representation of each user in a user list based on current task state data of each user in the user list and historical task completion data of each user in the user list;
the matching unit is used for matching the task keywords with the user portrait of each user in the user list and determining a target portrait matched with the task keywords;
and the distribution unit is used for distributing the work task to the user corresponding to the target image.
8. The task assigning apparatus of claim 7, wherein the generating unit, when configured to generate the user representation for each user in the user list based on current task state data for each user in the user list and historical task completion data for each user in the user list, is specifically configured to:
generating a user representation of each user in the user list based on a task list being processed by each user in the user list, a task progress of each task in the task list, a historical task processing performance of each user in the user list, and a historical task processing quality of each user in the user list.
9. A task allocation device, comprising a memory, a processor and a transceiver which are sequentially connected in communication, wherein the memory is used for storing a computer program, the transceiver is used for sending and receiving messages, and the processor is used for reading the computer program and executing the task allocation method according to any one of claims 1 to 6.
10. A computer-readable storage medium having stored thereon instructions for performing a method of task assignment as claimed in any one of claims 1 to 6 when run on a computer.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115600985A (en) * | 2022-10-27 | 2023-01-13 | 深圳标普云科技有限公司（Cn） | Online platform task management method and system |
| CN116663853A (en) * | 2023-07-24 | 2023-08-29 | 太平金融科技服务（上海）有限公司 | Task assigning method, device, computer equipment and storage medium |
| CN116720645A (en) * | 2022-10-21 | 2023-09-08 | 荣耀终端有限公司 | Task distribution method, distribution equipment and task distribution system |
| CN117391388A (en) * | 2023-11-09 | 2024-01-12 | 北京易华录信息技术股份有限公司 | Task distribution method and platform based on cloud computing |
| WO2024055963A1 (en) * | 2022-09-13 | 2024-03-21 | 华为云计算技术有限公司 | Task allocation method and apparatus |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109871492A (en) * | 2018-12-24 | 2019-06-11 | 深圳市珍爱捷云信息技术有限公司 | Task processing method, device, computer equipment and computer storage medium |
| CN110414864A (en) * | 2019-08-02 | 2019-11-05 | 深圳前海微众银行股份有限公司 | Method for allocating tasks, device, terminal and storage medium |
| CN110765760A (en) * | 2019-09-03 | 2020-02-07 | 平安科技（深圳）有限公司 | Legal case distribution method and device, storage medium and server |
-
2020
- 2020-09-29 CN CN202011054587.6A patent/CN112150023A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109871492A (en) * | 2018-12-24 | 2019-06-11 | 深圳市珍爱捷云信息技术有限公司 | Task processing method, device, computer equipment and computer storage medium |
| CN110414864A (en) * | 2019-08-02 | 2019-11-05 | 深圳前海微众银行股份有限公司 | Method for allocating tasks, device, terminal and storage medium |
| CN110765760A (en) * | 2019-09-03 | 2020-02-07 | 平安科技（深圳）有限公司 | Legal case distribution method and device, storage medium and server |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024055963A1 (en) * | 2022-09-13 | 2024-03-21 | 华为云计算技术有限公司 | Task allocation method and apparatus |
| CN116720645A (en) * | 2022-10-21 | 2023-09-08 | 荣耀终端有限公司 | Task distribution method, distribution equipment and task distribution system |
| CN115600985A (en) * | 2022-10-27 | 2023-01-13 | 深圳标普云科技有限公司（Cn） | Online platform task management method and system |
| CN115600985B (en) * | 2022-10-27 | 2023-09-15 | 深圳标普云科技有限公司 | On-line platform task management method and system |
| CN116663853A (en) * | 2023-07-24 | 2023-08-29 | 太平金融科技服务（上海）有限公司 | Task assigning method, device, computer equipment and storage medium |
| CN116663853B (en) * | 2023-07-24 | 2023-10-24 | 太平金融科技服务（上海）有限公司 | Task assigning method, device, computer equipment and storage medium |
| CN117391388A (en) * | 2023-11-09 | 2024-01-12 | 北京易华录信息技术股份有限公司 | Task distribution method and platform based on cloud computing |
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