Four-quadrant-based task processing method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a task processing method and device based on four quadrants, equipment and a storage medium. The method comprises the steps of obtaining task processing historical data of a current cluster, and generating quadrant key features corresponding to each quadrant in four quadrants according to the task processing historical data; for any task of the current cluster, matching task features of the task with the key features of each quadrant to obtain a matching result; and distributing the task to a target quadrant of the four quadrants for display according to a matching result. On the basis, the quadrant key features more fitting the cluster can be generated for each quadrant of the four quadrants based on the task processing historical data of the current cluster, so that quadrant distribution and display are performed on the tasks of the cluster based on the quadrant key features, the adaptability of the four quadrants to task processing of different clusters is improved, and the task processing efficiency is improved. Therefore, the task processing efficiency is improved more securely in a four-quadrant mode.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of task management, and in particular, to a task processing method, device, equipment and storage medium based on four quadrants. Background Art

[0002] With the popularization of online office, employee tasks are usually released in an online system to achieve collaborative office. With the development of clusters such as enterprises or organizations, the tasks in the online system may become more and more complicated. Some clusters usually set time nodes for tasks so that the processors can complete the corresponding tasks according to the time nodes.

[0003] However, with the increase in the number of tasks, the tasks at the same time node will also increase, which will cause confusion for the processors about the processing order of these tasks at the same time node, and may thus affect the task processing efficiency. Summary of the Invention

[0004] The embodiments of the present application provide a task processing method, device, equipment and storage medium based on four quadrants to improve task processing efficiency.

[0005] In a first aspect, the embodiments of the present application provide a task processing method based on four quadrants, and the method includes:

[0006] Obtain the task processing historical data of the current cluster, and generate the quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data;

[0007] For any task of the current cluster, match the task features of the task with the quadrant key features to obtain a matching result;

[0008] Allocate the task to the target quadrant in the four quadrants for display according to the matching result.

[0009] In a second aspect, the embodiments of the present application provide a task processing device based on four quadrants, and the device includes:

[0010] An acquisition and generation module, configured to obtain the task processing historical data of the current cluster, and generate the quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data;

[0011] A matching module, configured to match the task features of any task of the current cluster with the quadrant key features to obtain a matching result;

[0012] A display module, configured to allocate the task to the target quadrant in the four quadrants for display according to the matching result.

[0013] In a third aspect, the embodiments of the present application further provide an electronic device, and the electronic device includes:

[0014] One or more processors;

[0015] A storage device for storing one or more programs,

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the quadrant-based task processing method provided in any embodiment of the present application.

[0017] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and characterized in that when the program is executed by a processor, it implements the quadrant-based task processing method provided in any embodiment of the present application.

[0018] The technical solution of the embodiment of the present application is to obtain the task processing historical data of the current cluster, and generate the respective quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data; for any task of the current cluster, match the task features of the task with the quadrant key features to obtain a matching result; and allocate the task to the target quadrant in the four quadrants for display according to the matching result. Based on this, the present application can generate more cluster-adapted quadrant key features for each quadrant of the four quadrants based on the task processing historical data of the current cluster, so as to perform quadrant allocation and display of the tasks of the cluster based on the quadrant key features, improve the adaptability of the four quadrants to different cluster task processing, so that the processor can process the tasks based on the four quadrants, and improve the efficiency of task processing. Description of the Drawings

[0019] Figure 1 It is a schematic flow chart of the quadrant-based task processing method provided in Embodiment 1 of the present application;

[0020] Figure 2 It is a schematic structural diagram of a quadrant-based task processing device provided in Embodiment 2 of the present application;

[0021] Figure 3 It is a schematic structural diagram of an electronic device provided in Embodiment 3 of the present application. Detailed Embodiments

[0022] The present application will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present application, rather than limiting the present application. Additionally, it should be noted that for the sake of convenience of description, only parts related to the present application are shown in the drawings rather than all the structures.

[0023] Embodiment 1

[0024] Figure 1The flowchart of the task processing method based on four quadrants provided in the first embodiment of this application is as follows: Figure 1 As shown in Figure 1 , the task processing method based on four quadrants provided in this embodiment can be applied to a task processing platform based on four quadrants installed on a device with data processing capabilities such as a computer, and can cooperate with some application software to achieve a better experience. Specifically, it can include the following steps:

[0025] Step 101: Obtain the historical data of task processing of the current cluster, and generate the corresponding key features of each quadrant in the four quadrants according to the historical data of task processing.

[0026] In this step, the cluster can refer to a company, enterprise, organization, department, or even a group. Since each cluster has different requirements for its own task processing, this embodiment will generate different key features of the quadrants based on the uniqueness of each cluster, so that the task grouping is more in line with the needs of the current cluster.

[0027] Specifically, the historical data of task processing includes the historical task details and the historical task processing progress details corresponding to each historical task. When generating the key features of each quadrant, feature extraction can be performed on the historical task details and the historical task processing progress details of each historical task to obtain the task features and task processing features corresponding to each historical task; iterative classification is performed based on the task features and the corresponding task processing features until 4 category sets are obtained; for any category set, the common features of the historical tasks in the set are determined as the key features of any quadrant in the four quadrants.

[0028] Among them, the historical task details usually can include several of the following information: task content, task deadline, cycle nature, collaboration nature, etc.; the historical task processing progress details can include several of the following information: processing conclusion (such as completion, forwarding to others for continued processing, etc.), processing time consumption (the time consumed from the generation of the task to the completion).

[0029] When performing feature extraction, for the historical task details, usually its structural features and content features are extracted as task features. Among them, the structural feature is the information structure contained in the task. For example, it contains two pieces of information: task content and cycle nature. The content feature mainly focuses on the deadline, such as the time duration between the generation time and the completion deadline of the task.

[0030] For the historical task processing progress details, usually its content features are extracted as task processing features. For example, it takes a certain period of time to complete, or it takes a certain period of time to be transferred to someone.

[0031] After extracting the features, each historical task will have its own task features and task processing features, and based on these features, the historical tasks can be clustered. Specifically, the Gaussian mixture model can be used to iteratively cluster the historical tasks based on the task features and the corresponding task processing features; when four category sets are clustered, the iteration stops.

[0032] Since this application is for classifying tasks based on the four quadrants, therefore, the result of the iteration in this embodiment needs to meet the condition of finally including four categories, that is, classifying the historical tasks into four categories.

[0033] Specifically, when using the Gaussian mixture model for classification, the model can be initialized first. For example, the number of clusters (4 in this embodiment) can be set first, and the parameters of the Gaussian distribution can be initialized, and then the expectation-maximization algorithm is used for iteration, and the logarithmic likelihood function is used for convergence judgment. Finally, the historical tasks are divided into the category with the largest posterior probability, and after the assignment is completed, the clustering is completed.

[0034] After completing the clustering, the common features of the historical tasks in each set can be determined as the key features of any quadrant of the four quadrants. It should be noted that the common feature can be the task feature that appears the most in the set.

[0035] In a specific example, the first quadrant can be tasks that the person needs to actually process, are periodic and have a long period. The key features of the quadrant it contains can be the period feature and the period is greater than half a year, and the collaboration feature indicates that it is completed by oneself (the quadrant can be defined as "often do"). The second quadrant can be tasks that the person needs to actually process and have a short deadline (the quadrant can be defined as "do on time"), the third quadrant can be tasks that the person does not need to actually process but have a short deadline (the quadrant can be defined as "do every day"), and the fourth quadrant can be tasks that the person does not need to actually process and have a long deadline (the quadrant can be defined as "authorized to do").

[0036] Step 102: For any task in the current cluster, match the task features of the task with the key features of each quadrant to obtain a matching result.

[0037] In this step, for any task in the current cluster, the similarity between the task features of the task and the key features of each quadrant can be determined; the similarity corresponding to each quadrant is determined as the matching result of the task.

[0038] Among them, for the extraction of the task features of the task, reference can be made to the extraction of the task features of the historical tasks described above, which will not be elaborated here.

[0039] In addition, when determining the similarity, for any quadrant, the similarity between the task features and the key features of the quadrant can be analogized in sequence, and then the features exceeding the preset similarity value are determined as similar features, and the ratio of the number of similar features to the number of key features of the quadrant is determined as the similarity of the quadrant.

[0040] Step 103: Assign the task to the target quadrant of the four quadrants for display according to the matching result.

[0041] In this step, the task can be assigned to the quadrant corresponding to the highest similarity and displayed according to the preset display method. Among them, the preset display method can be sorted display. For example, the user operation information of the task can be obtained, and the current tasks in the quadrant can be sorted and displayed according to the user operation information.

[0042] Among them, the user operation information can include the number of clicks on each task by the user. Generally, for tasks that are more important to the user, the user's attention degree is higher, and the corresponding number of clicks will also be higher. Therefore, the number of clicks can be used as the basis for sorting.

[0043] In addition, the processing behavior data of the historical tasks in the quadrant by the user can be obtained, and the priority of various tasks in the quadrant can be assigned according to the processing behavior data; the tasks are displayed according to the priority of the task category.

[0044] Here, it is mainly to classify the tasks in the quadrant in more detail. For the categories that the user pays more attention to, a higher priority is set. The higher the priority, the more prominent the display.

[0045] In this embodiment, the task processing historical data of the current cluster is obtained, and the key features corresponding to each quadrant in the four quadrants are generated according to the task processing historical data; for any task in the current cluster, the task features of the task are matched with the key features of each quadrant to obtain a matching result; the task is assigned to the target quadrant of the four quadrants for display according to the matching result. Based on this, the present application can generate key features of each quadrant of the four quadrants that are more suitable for the cluster based on the task processing historical data of the current cluster, so as to perform quadrant assignment and display of the tasks of the cluster based on the key features of the quadrant, improve the adaptability of the four quadrants to the task processing of different clusters, so that the processor can process the tasks based on the four quadrants, improve the efficiency of task processing, and it is more reliable to use the four quadrant method to improve the task processing efficiency.

[0046] Embodiment 2

[0047] Figure 2The figure is a schematic structural diagram of a task processing device based on four quadrants provided in the second embodiment of the present application. The task processing device based on four quadrants provided in the embodiments of the present application can execute the task processing method based on four quadrants provided in any embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. The device can be implemented in software and / or hardware, such as Figure 2 As shown, the task processing device based on four quadrants specifically includes: an acquisition and generation module 201, a matching module 202, and a display module 203.

[0048] Among them, the acquisition and generation module is used to acquire the task processing historical data of the current cluster, and generate the corresponding key features of each quadrant in the four quadrants according to the task processing historical data;

[0049] The matching module is used to match the task features of any task in the current cluster with the key features of each quadrant to obtain a matching result;

[0050] The display module is used to display the task in the target quadrant of the four quadrants according to the matching result.

[0051] In this embodiment, the task processing historical data of the current cluster is acquired, and the corresponding key features of each quadrant in the four quadrants are generated according to the task processing historical data; for any task in the current cluster, the task features of the task are matched with the key features of each quadrant to obtain a matching result; the task is displayed in the target quadrant of the four quadrants according to the matching result. Based on this, the present application can generate more cluster-adapted key features for each quadrant of the four quadrants based on the task processing historical data of the current cluster, so as to perform quadrant allocation and display of the tasks of the cluster based on the key features of the quadrant, improve the adaptability of the four quadrants to different cluster task processing, so that the processor can process the tasks based on the four quadrants, improve the efficiency of task processing, and it is more reliable to use the four quadrant method to improve the task processing efficiency.

[0052] Further, the task processing historical data includes the historical task details and the historical task processing progress details corresponding to each historical task;

[0053] The acquisition and generation module is specifically used for:

[0054] Extract the features of the historical task details and the historical task processing progress details of each historical task to obtain the task features and task processing features corresponding to each historical task;

[0055] Perform iterative classification based on the task features and the corresponding task processing features until 4 category sets are obtained;

[0056] For any category set, determine the common characteristics of the historical tasks in the set as the key characteristics of any quadrant in the four quadrants.

[0057] Further, the obtaining and generating module is specifically configured to:

[0058] Use the Gaussian mixture model to perform iterative clustering on historical tasks based on task characteristics and corresponding task processing characteristics;

[0059] Stop the iteration when four category sets are clustered.

[0060] Further, the matching module is specifically configured to:

[0061] For any task in the current cluster, determine the similarity between the task characteristics of the task and the key characteristics of each quadrant;

[0062] Determine the similarity corresponding to each quadrant as the matching result of the task.

[0063] Further, the matching result includes the similarity corresponding to each quadrant;

[0064] The display module is specifically configured to:

[0065] Assign the task to the quadrant corresponding to the highest similarity and display the task according to a preset display method.

[0066] Further, the display module is specifically configured to:

[0067] Obtain the user operation information of the task and sort and display the current tasks in the quadrant according to the user operation information.

[0068] Further, the display module is specifically configured to:

[0069] Obtain the processing behavior data of the historical tasks of the user in the quadrant and assign priorities to various tasks in the quadrant according to the processing behavior data;

[0070] Display the tasks according to the priorities of the categories to which the tasks belong.

[0071] Embodiment III

[0072] Figure 3 FIG. is a schematic structural diagram of an electronic device provided in Embodiment III of the present application. As Figure 3 shown, the electronic device includes a processor 310, a memory 320, an input device 330, and an output device 340; the number of processors 310 in the electronic device may be one or more. Figure 3 Taking one processor 310 as an example; the processor 310, the memory 320, the input device 330, and the output device 340 in the electronic device may be connected through a bus or other means.Figure 3 Take the bus connection as an example.

[0073] As a computer-readable storage medium, the memory 320 can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the quadrant-based task processing method in the embodiments of the present invention. By running the software programs, instructions, and modules stored in the memory 320, the processor 310 can execute various functional applications and data processing of the electronic device, that is, implement the above-mentioned quadrant-based task processing method:

[0074] Obtain the task processing historical data of the current cluster, and generate the respective quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data;

[0075] For any task in the current cluster, match the task features of the task with the respective quadrant key features to obtain a matching result;

[0076] Allocate the task to the target quadrant in the four quadrants for display according to the matching result.

[0077] In this embodiment, obtain the task processing historical data of the current cluster, and generate the respective quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data; for any task in the current cluster, match the task features of the task with the respective quadrant key features to obtain a matching result; allocate the task to the target quadrant in the four quadrants for display according to the matching result. Based on this, the present application can generate quadrant key features that are more suitable for the cluster for each quadrant in the four quadrants based on the task processing historical data of the current cluster, so as to perform quadrant allocation and display of the tasks of the cluster based on the quadrant key features, improve the adaptability of the four quadrants to the task processing of different clusters, and thus make it more reliable to use the four quadrants to improve the task processing efficiency.

[0078] Furthermore, the task processing historical data includes the historical task details and historical task processing progress details corresponding to each historical task;

[0079] Generating the respective quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data includes:

[0080] Extract features from the historical task details and historical task processing progress details of each historical task to obtain the task features and task processing features corresponding to each historical task;

[0081] Perform iterative classification based on the task features and corresponding task processing features until 4 category sets are obtained;

[0082] For any category set, determine the common features of the historical tasks in the set as the quadrant key feature of any quadrant in the four quadrants.

[0083] Further, iterative classification is performed based on the task characteristics and the corresponding task processing characteristics until four category sets are obtained, including:

[0084] Using the Gaussian mixture model, iterative clustering is performed on historical tasks based on the task characteristics and the corresponding task processing characteristics;

[0085] When four category sets are clustered, the iteration is stopped.

[0086] Further, for any task in the current cluster, the task characteristics of the task are matched with the key characteristics of each quadrant to obtain a matching result, including:

[0087] For any task in the current cluster, determine the similarity between the task characteristics of the task and the key characteristics of each quadrant;

[0088] Determine the similarity corresponding to each quadrant as the matching result of the task.

[0089] Further, the matching result includes the similarity corresponding to each quadrant;

[0090] According to the matching result, the task is assigned to the target quadrant of the four quadrants for display, including:

[0091] Assign the task to the quadrant corresponding to the highest similarity and display the task according to the preset display method.

[0092] Further, display the task according to the preset display method, including:

[0093] Obtain the user operation information of the task and sort and display the current tasks within the quadrant according to the user operation information.

[0094] Further, display the task according to the preset display method, including:

[0095] Obtain the processing behavior data of the historical tasks of the user in the quadrant and assign priorities to various tasks in the quadrant according to the processing behavior data;

[0096] Display the task according to the priority of the category to which the task belongs.

[0097] The memory 320 may mainly include a program storage area and a data storage area. Among them, 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 according to the use of the terminal, etc. In addition, the memory 320 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 devices. In some instances, the memory 320 may further include a memory remotely provided with respect to the processor 310, and these remote memories may be connected to the electronic device through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0098] Embodiment 4

[0099] Embodiment 4 of the present application further provides a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute a quadrant-based task processing method when executed by a computer processor. The method includes:

[0100] Obtain the task processing historical data of the current cluster, and generate respective quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data;

[0101] For any task of the current cluster, match the task features of the task with the respective quadrant key features to obtain a matching result;

[0102] Allocate the task to the target quadrant in the four quadrants for display according to the matching result.

[0103] In this embodiment, the task processing historical data of the current cluster is obtained, and respective quadrant key features corresponding to each quadrant in the four quadrants are generated according to the task processing historical data; for any task of the current cluster, the task features of the task are matched with the respective quadrant key features to obtain a matching result; the task is allocated to the target quadrant in the four quadrants for display according to the matching result. Based on this, the present application can generate more cluster-adapted quadrant key features for each quadrant of the four quadrants based on the task processing historical data of the current cluster, so as to perform quadrant allocation and display of the tasks of the cluster based on the quadrant key features, improve the adaptability of the four quadrants to different cluster task processing, and thus make it more reliable to use the four quadrants to improve task processing efficiency.

[0104] Further, the task processing historical data includes the historical task details and historical task processing progress details respectively corresponding to each historical task;

[0105] Generating respective quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data includes:

[0106] Feature extraction is performed on the historical task details and historical task processing progress details of each historical task to obtain the task features and task processing features corresponding to each historical task;

[0107] Based on the task features and the corresponding task processing features, iterative classification is performed until 4 category sets are obtained;

[0108] For any category set, the common features of the historical tasks in the set are determined as the quadrant key features of any quadrant in the four quadrants.

[0109] Furthermore, based on the task features and the corresponding task processing features, iterative classification is performed until 4 category sets are obtained, including:

[0110] Using the Gaussian mixture model, iterative clustering is performed on the historical tasks based on the task features and the corresponding task processing features;

[0111] When 4 category sets are clustered, the iteration stops.

[0112] Furthermore, for any task in the current cluster, the task features of the task are matched with the quadrant key features to obtain the matching results, including:

[0113] For any task in the current cluster, the similarity between the task features of the task and the quadrant key features is determined;

[0114] The similarity corresponding to each quadrant is determined as the matching result of the task.

[0115] Furthermore, the matching results include the similarity corresponding to each quadrant;

[0116] According to the matching results, the task is assigned to the target quadrant in the four quadrants for display, including:

[0117] The task is assigned to the quadrant with the highest similarity and displayed according to the preset display method.

[0118] Furthermore, displaying the task according to the preset display method includes:

[0119] Obtain the user operation information of the task and sort and display the current tasks within the quadrant according to the user operation information.

[0120] Furthermore, displaying the task according to the preset display method includes:

[0121] Obtain the processing behavior data of the user on the historical tasks in the quadrant and assign priorities to various tasks in the quadrant according to the processing behavior data;

[0122] Display the tasks according to the priorities of the task categories to which the tasks belong.

[0123] Certainly, for the storage medium containing computer-executable instructions provided in the embodiments of the present application, the computer-executable instructions are not limited to the above method operations, and can also execute the related operations in the task processing method based on four quadrants provided in any embodiment of the present application.

[0124] From the above description of the embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software and necessary general hardware. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disc of a computer, etc., including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present application.

[0125] It should be noted that in the embodiments of the above search device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present application.

[0126] Note that the above is only the preferred embodiment of the present application and the applied technical principle. Those skilled in the art will understand that the present application is not limited to the specific embodiments here, and various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments. Without departing from the concept of the present application, more other equivalent embodiments can be included, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A task processing method based on four quadrants, characterized in that, The method includes: Obtaining the task processing historical data of the current cluster, and generating the quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data; For any task in the current cluster, matching the task features of the task with each of the quadrant key features to obtain a matching result; Allocating the task to the target quadrant of the four quadrants for display according to the matching result.

2. The method according to claim 1, wherein The task processing historical data includes the historical task details and the historical task processing progress details corresponding to each historical task; The generating the quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data includes: Performing feature extraction on the historical task details and the historical task processing progress details of each historical task to obtain the task features and the task processing features corresponding to each historical task; Performing iterative classification based on the task features and the corresponding task processing features until 4 category sets are obtained; For any category set, determining the common features of the historical tasks in the set as the quadrant key features of any quadrant in the four quadrants.

3. The method according to claim 2, characterized in that, The performing iterative classification based on the task features and the corresponding task processing features until 4 category sets are obtained includes: Using a Gaussian mixture model, performing iterative clustering on the historical tasks based on the task features and the corresponding task processing features; Stopping the iteration when 4 category sets are clustered.

4. The method according to claim 1, wherein The matching the task features of the task with each of the quadrant key features to obtain a matching result for any task in the current cluster includes: For any task in the current cluster, determining the similarity between the task features of the task and each of the quadrant key features; Determining the similarity corresponding to each quadrant as the matching result of the task.

5. The method according to claim 1, wherein The matching result includes the similarity corresponding to each quadrant; The allocating the task to the target quadrant of the four quadrants for display according to the matching result includes: Allocating the task to the quadrant with the highest similarity, and displaying the task according to a preset display method.

6. The method according to claim 5, characterized in that, The displaying the task according to a preset display method includes: Obtaining the user operation information of the task, and sorting and displaying the current tasks in the quadrant according to the user operation information.

7. The method according to claim 5, wherein The displaying the task according to a preset display method includes: Obtaining the processing behavior data of the user for the historical tasks in the quadrant, and assigning priorities to various tasks in the quadrant according to the processing behavior data; Displaying the task according to the priority of the category to which the task belongs.

8. A task processing device based on four quadrants, characterized in that, The device includes: An acquisition and generation module, configured to obtain the task processing historical data of the current cluster, and generate the quadrant key features corresponding to each quadrant in the four quadrants according to the task processing historical data; A matching module, configured to match the task features of any task in the current cluster with each of the quadrant key features to obtain a matching result; A display module, configured to allocate the task to the target quadrant of the four quadrants for display according to the matching result.

9. An electronic device, characterized in that, Includes: One or more processors; A storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, such that the one or more processors implement the quadrant-based task processing method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the quadrant-based task processing method according to any one of claims 1-7.

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