CN110764898A

CN110764898A - Task allocation method and device, readable storage medium and terminal equipment

Info

Publication number: CN110764898A
Application number: CN201910824396.4A
Authority: CN
Inventors: 王培强; 李亮
Original assignee: Ping An Technology Shenzhen Co Ltd
Current assignee: Ping An Technology Shenzhen Co Ltd
Priority date: 2019-09-02
Filing date: 2019-09-02
Publication date: 2020-02-07
Anticipated expiration: 2039-09-02
Also published as: CN110764898B; WO2021043057A1

Abstract

The present invention relates to the field of data processing technologies, and in particular, to a method and an apparatus for task allocation, a storage medium, and a terminal device. The method comprises the following steps: acquiring tasks to be distributed from a preset task queue according to a specified sequence; determining a multi-dimensional first attribute characteristic corresponding to a task to be distributed, and performing dimension reduction processing on the multi-dimensional first attribute characteristic to obtain a plurality of one-dimensional first attribute characteristics; acquiring preset multidimensional second attribute characteristics of each task processing group, and performing dimension reduction processing on the multidimensional second attribute characteristics to obtain a plurality of one-dimensional second attribute characteristics corresponding to each task processing group; determining a processing thread corresponding to each task processing group, analyzing each one-dimensional first attribute feature and each one-dimensional second attribute feature by adopting the processing thread, and determining a matching value between the task to be distributed and each task processing group; and determining a first task processing group matched with the task to be distributed according to the matching value, and sending the task to be distributed to a terminal corresponding to the first task processing group.

Description

Task allocation method and device, readable storage medium and terminal equipment

Technical Field

The present invention relates to the field of data processing technologies, and in particular, to a method and an apparatus for task allocation, a computer-readable storage medium, and a terminal device.

Background

In the current task or job allocation, the tasks are generally allocated randomly or only according to a single attribute such as the task type of the task, that is, the tasks are allocated according to a preset corresponding relationship between the single attribute such as the task type and the task processing group.

In conclusion, how to improve the reasonability and the distribution efficiency of task distribution becomes a problem to be solved urgently by the technical personnel in the field.

Disclosure of Invention

Embodiments of the present invention provide a task allocation method and apparatus, a computer-readable storage medium, and a terminal device, which can implement accurate matching between a task to be allocated with a multidimensional attribute feature and a task processing group with the multidimensional attribute feature, and improve the reasonability and allocation efficiency of task allocation.

In a first aspect of the embodiments of the present invention, a task allocation method is provided, including:

acquiring tasks to be distributed from a preset task queue according to a specified sequence;

determining a multi-dimensional first attribute characteristic corresponding to the task to be distributed, and performing dimension reduction processing on the multi-dimensional first attribute characteristic to obtain a plurality of one-dimensional first attribute characteristics corresponding to the task to be distributed;

acquiring preset multi-dimensional second attribute characteristics corresponding to each task processing group, and performing dimension reduction processing on the multi-dimensional second attribute characteristics to respectively obtain a plurality of one-dimensional second attribute characteristics corresponding to each task processing group;

determining a processing thread corresponding to each task processing group, analyzing the plurality of one-dimensional first attribute features of the task to be distributed and the plurality of one-dimensional second attribute features of the task processing group corresponding to the processing thread by adopting the processing thread, and determining a matching value between the task to be distributed and each task processing group;

and determining a first task processing group matched with the task to be distributed in the task processing groups according to the matching value, and sending the task to be distributed to a terminal corresponding to the first task processing group so as to indicate the terminal to process the task to be distributed.

In a second aspect of the embodiments of the present invention, there is provided a task allocation apparatus, including:

the task to be distributed acquisition module is used for acquiring tasks to be distributed from a preset task queue according to a specified sequence;

the first attribute feature dimension reduction module is used for determining a multi-dimensional first attribute feature corresponding to the task to be distributed and performing dimension reduction processing on the multi-dimensional first attribute feature to obtain a plurality of one-dimensional first attribute features corresponding to the task to be distributed;

the second attribute feature dimension reduction module is used for acquiring multi-dimensional second attribute features corresponding to preset task processing groups, and performing dimension reduction processing on the multi-dimensional second attribute features to respectively obtain a plurality of one-dimensional second attribute features corresponding to the task processing groups;

a matching value determining module, configured to determine a processing thread corresponding to each task processing group, analyze, by using the processing thread, the multiple one-dimensional first attribute features of the task to be allocated and the multiple one-dimensional second attribute features of the task processing group corresponding to the processing thread, and determine a matching value between the task to be allocated and each task processing group;

and the task allocation module is used for determining a first task processing group matched with the task to be allocated in the task processing groups according to the matching value, and sending the task to be allocated to a terminal corresponding to the first task processing group so as to instruct the terminal to process the task to be allocated.

In a third aspect of the embodiments of the present invention, a computer-readable storage medium is provided, where computer-readable instructions are stored, and the computer-readable instructions, when executed by a processor, implement the steps of the task allocation method according to the first aspect.

In a fourth aspect of the embodiments of the present invention, there is provided a terminal device, including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor, where the processor executes the computer-readable instructions to implement the following steps:

According to the technical scheme, the embodiment of the invention has the following advantages:

after the tasks to be allocated are obtained from the preset task queue according to the designated sequence, the multi-dimensional first attribute characteristics corresponding to the tasks to be allocated can be firstly determined, the multi-dimensional first attribute characteristics of the tasks to be allocated are subjected to dimension reduction processing to obtain a plurality of one-dimensional first attribute characteristics corresponding to the tasks to be allocated, meanwhile, the multi-dimensional second attribute characteristics corresponding to each task processing group can also be obtained, the dimension reduction processing is performed on each multi-dimensional second attribute characteristic to obtain a plurality of one-dimensional second attribute characteristics corresponding to each task processing group, when the tasks to be allocated are matched with each task processing group, the matching values between the tasks to be allocated and each task processing group can be determined by adopting a multi-processing thread parallel mode, namely, the processing threads corresponding to each task processing group are determined, and the plurality of one-dimensional first attribute characteristics of the tasks to be allocated and the plurality of one-dimensional second attribute characteristics of each task processing group are respectively adopted to analyze, the task processing group matched with the task to be distributed is determined according to the matching value, the task to be distributed with the multi-dimensional attribute characteristic and the task processing group with the multi-dimensional attribute characteristic are accurately matched, the task distribution rationality is improved, meanwhile, matching is carried out through multi-thread parallel, the matching efficiency can be improved, and therefore the task distribution efficiency is improved. In addition, the multidimensional attribute features are subjected to dimension reduction processing, so that the matching values are determined through the dimension-reduced one-dimensional attribute features, the calculation complexity of the matching values can be greatly reduced, and the distribution efficiency of task distribution is improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

FIG. 1 is a flowchart of an embodiment of a task allocation method according to an embodiment of the present invention;

fig. 2 is a schematic flow chart illustrating a task allocation method for determining a matching value in an application scenario according to an embodiment of the present invention;

fig. 3 is a schematic flowchart illustrating a task allocation method for determining a first task processing group in an application scenario according to an embodiment of the present invention;

FIG. 4 is a block diagram of an embodiment of a task assigning apparatus according to an embodiment of the present invention;

fig. 5 is a schematic diagram of a terminal device according to an embodiment of the present invention.

Detailed Description

The embodiment of the invention provides a task allocation method and device, a computer readable storage medium and terminal equipment, which are used for realizing the accurate matching between a task to be allocated with a multi-dimensional attribute characteristic and a task processing group with the multi-dimensional attribute characteristic and improving the reasonability and the allocation efficiency of task allocation.

In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. Furthermore, the terms "first," "second," and "third," etc. are used to distinguish between different objects and are not used to describe a particular order.

Referring to fig. 1, an embodiment of the present invention provides a task allocation method, where the task allocation method includes:

s101, acquiring tasks to be distributed from a preset task queue according to a specified sequence;

the execution subject of the embodiment of the invention is terminal equipment, and the terminal equipment comprises but is not limited to: desktop computers, notebooks, palm computers, cloud servers, and other computing devices. When a user needs to perform task allocation, the user can upload or send tasks to be allocated to the terminal device, wherein the first attribute features of the uploaded or sent tasks to be allocated are often multi-dimensional attribute features, when the terminal device receives the tasks to be allocated, the tasks to be allocated can be stored in a preset task queue of the terminal device, and for example, the tasks to be allocated can be sequentially stored in the preset task queue according to the uploading time of the tasks to be allocated. Further, when storing each task to be allocated to the preset task queue, the terminal device may further set a designated sequence for the preset task queue, so as to obtain the task to be allocated from the preset task queue according to the designated sequence, where the designated sequence may be a sequence in which task obtaining is performed according to the upload time of each task to be allocated, for example, a task to be allocated which is earlier in upload time is obtained earlier, and the designated sequence may also be a sequence in which task obtaining is performed according to the importance of each task to be allocated, for example, a task to be allocated which is higher in importance is obtained earlier. Therefore, when the task is allocated, the terminal device may sequentially obtain the tasks to be allocated from the preset task queue according to the designated sequence.

Step S102, determining a multi-dimensional first attribute characteristic corresponding to the task to be distributed, and performing dimension reduction processing on the multi-dimensional first attribute characteristic to obtain a plurality of one-dimensional first attribute characteristics corresponding to the task to be distributed;

it can be understood that, after the terminal device obtains the task to be allocated from the preset task queue, it may further determine a multi-dimensional first attribute feature corresponding to the task to be allocated, and perform a dimension reduction process on the multi-dimensional first attribute feature to obtain a plurality of one-dimensional first attribute features corresponding to the task to be allocated, for example, a linear dimension reduction method may be used to abstract the multi-dimensional first attribute feature into a two-dimensional array, where each data item in the two-dimensional array is a one-dimensional first attribute feature. Here, the linear dimension reduction method may be an existing commonly used linear dimension reduction method.

Step S103, acquiring preset multi-dimensional second attribute characteristics corresponding to each task processing group, and performing dimension reduction processing on the multi-dimensional second attribute characteristics to respectively obtain a plurality of one-dimensional second attribute characteristics corresponding to each task processing group;

in the embodiment of the invention, a plurality of task processing groups for processing different types of tasks can be preset, such as a plurality of task processing groups for processing vehicle insurance tasks, a plurality of task processing groups for processing human insurance tasks, a plurality of task processing groups for processing property insurance tasks and the like, wherein the second attribute characteristics corresponding to each task processing group are multidimensional attribute characteristics, namely, the task processing groups can be matched by matching the multidimensional second attribute characteristics. Therefore, when the task to be allocated needs to be allocated, the terminal device may first obtain the multidimensional second attribute features corresponding to each task processing group, and then may perform dimension reduction processing on the multidimensional second attribute features of each task processing group to reduce the dimension of the multidimensional second attribute features of each task processing group into a plurality of one-dimensional second attribute features, for example, the multidimensional second attribute features of each task processing group may be similarly reduced into a plurality of one-dimensional second attribute features corresponding to the task processing group by using a linear dimension reduction method.

Preferably, in the embodiment of the present invention, the acquiring a multidimensional second attribute characteristic corresponding to each preset task processing group may include: and extracting second attribute features of the processing staff in each task processing group, and combining the extracted second attribute features to obtain multi-dimensional second attribute features corresponding to each task processing group.

Here, each task processing group may include a plurality of processing employees, each processing employee may have a second attribute feature corresponding to a task that can be processed by the processing employee, and the multidimensional second attribute feature corresponding to each task processing group may be obtained based on a combination of the second attribute features of the processing employees in the task processing group, that is, after determining the processing employees included in each task processing group, the second attribute feature corresponding to each processing employee may be extracted according to a task condition that can be processed by each processing employee in the task processing group, and then the second attribute features of the processing employees in the task processing group may be combined to obtain the multidimensional second attribute feature corresponding to the task processing group.

Specifically, in the embodiment of the present invention, the second attribute feature of each processing employee and the historical work data corresponding to each processing employee may be obtained, and each processing employee may be grouped according to the historical work data and the second attribute feature, so as to determine the processing employee included in each task processing group.

Step S104, determining a processing thread corresponding to each task processing group, analyzing the plurality of one-dimensional first attribute characteristics of the task to be distributed and the plurality of one-dimensional second attribute characteristics of the task processing group corresponding to the processing thread by adopting the processing thread, and determining a matching value between the task to be distributed and each task processing group;

it can be understood that after obtaining the plurality of one-dimensional first attribute features corresponding to the tasks to be allocated and the plurality of one-dimensional second attribute features corresponding to the task processing groups, a multi-thread parallel manner may be adopted to respectively determine the matching values between the tasks to be allocated and the task processing groups. Specifically, a processing thread corresponding to each task processing group may be determined first, and then, a plurality of one-dimensional first attribute features of the tasks to be allocated and a plurality of one-dimensional second attribute features of the corresponding task processing groups may be analyzed by using each processing thread to determine a matching value between the tasks to be allocated and each task processing group, that is, one processing thread may be used to determine a matching value between one task processing group and the tasks to be allocated. The process of determining the matching value by each processing thread may be: firstly, the corresponding relation between each one-dimensional second attribute feature in a task processing group and each one-dimensional first attribute feature in a task to be distributed is determined, then the similarity between the one-dimensional second attribute feature and the one-dimensional first attribute feature which have the corresponding relation in the task processing group and the task to be distributed is calculated, and finally the similarity corresponding to the task processing group can be weighted and summed to obtain the matching value between the task to be distributed and the task processing group.

Specifically, as shown in fig. 2, the analyzing, by using the processing thread, the plurality of one-dimensional first attribute features of the task to be allocated and the plurality of one-dimensional second attribute features of the task processing group corresponding to the processing thread to determine the matching value between the task to be allocated and each task processing group may include:

step S201, determining each target one-dimensional first attribute characteristic and each target one-dimensional second attribute characteristic matched between the task to be distributed and the task processing group corresponding to the processing thread by using the processing thread, and respectively constructing a first characteristic matrix of each target one-dimensional first attribute characteristic and a second characteristic matrix of each target one-dimensional second attribute characteristic;

it is understood that, in the one-dimensional second attribute feature included in each task processing group, there will often be some or all of the same attribute features as the one-dimensional first attribute features included in the task to be assigned. Here, the matching value between the task to be allocated and a certain task processing group can be determined according to the same attribute characteristics of the two, that is, when determining the matching value between the task to be allocated and a certain task processing group, the processing thread corresponding to the task processing group may be used to determine each target one-dimensional first attribute feature and each target one-dimensional second attribute feature that are matched between the task to be allocated and the task processing group, wherein the one-dimensional first attribute feature of the target and the one-dimensional second attribute feature of the target are the same one-dimensional attribute feature, then, a first feature matrix of the one-dimensional first attribute features of each target can be respectively constructed according to the first feature values of the one-dimensional first attribute features of each target in the tasks to be distributed, meanwhile, a second feature matrix of the one-dimensional second attribute features of the targets can be respectively constructed according to second feature values of the one-dimensional second attribute features of the targets in the task processing group.

For example, in a specific scenario, if the task to be allocated includes A, B, C, D, E and F six one-dimensional first attribute features, and the task processing group S includes B, C, F, G, H, I and J seven one-dimensional second attribute features, it may be determined that B, C, F three identical one-dimensional attribute features exist between the task to be allocated and the task processing group S, that is, it may be determined that each target one-dimensional first attribute feature corresponding to the task to be allocated is B, C, F, and it may be determined that each target one-dimensional second attribute feature corresponding to the task processing group S is B, C, F, at this time, the first feature value B of the target one-dimensional first attribute feature B and the first feature value B of the target one-dimensional first attribute feature C of the task to be allocated may be obtainedThe eigenvalue c and the first eigenvalue F of the one-dimensional first attribute feature F of the target, and a first feature matrix Meanfeature corresponding to the one-dimensional first attribute feature B of the target can be constructed according to the first eigenvalue B_1BAnd constructing a first feature matrix Meanfeature corresponding to the one-dimensional first attribute feature C of the target according to the first feature value C_1CAnd constructing a first feature matrix MeanFeature corresponding to the one-dimensional first attribute feature F of the target according to the first feature value F_1FMeanwhile, a second eigenvalue B ' of the target one-dimensional second attribute feature B, a second eigenvalue C ' of the target one-dimensional second attribute feature C and a second eigenvalue F ' of the target one-dimensional second attribute feature F in the task processing group S can be obtained, and a second eigen matrix MeanFeature corresponding to the target one-dimensional second attribute feature B can be constructed according to the second eigenvalue B_2BAnd constructing a second feature matrix Meanfeature corresponding to the one-dimensional second attribute feature C of the target according to the second feature value C_2CAnd constructing a second feature matrix MeanFeature corresponding to the one-dimensional second attribute feature F of the target according to the second feature value F_2F。

Step S202, calculating the similarity between each first feature matrix and the corresponding second feature matrix;

in the embodiment of the present invention, after obtaining each first feature matrix and each corresponding second feature matrix, similarity between each first feature matrix and each corresponding second feature matrix may be calculated, and in the application scenario described in step S201, the first feature matrix MeanFeature may be calculated respectively_1BAnd the second feature matrix MeanFeature_2BSimilarity between, first feature matrix MeanFeature_1CAnd the second feature matrix MeanFeature_2CSimilarity between them and the first feature matrix MeanFeature_1FAnd the second feature matrix MeanFeature_2FThe similarity between them.

Preferably, in an embodiment of the present invention, the calculating the similarity between each first feature matrix and the corresponding second feature matrix may include:

calculating the similarity between each first feature matrix and the corresponding second feature matrix according to the following formula:

Matchpoint_i＝MeanFeature_1i*(MeanFeature_2i)^T

wherein, MatchPoint_iMeanfeature, which is the similarity between the ith first feature matrix and the corresponding second feature matrix_1iIs the ith first feature matrix, T is transposed symbol, Meanfeature_2iAnd the second characteristic matrix is corresponding to the ith first characteristic matrix.

It should be noted that, when determining a matching value between the task to be assigned and a certain task processing group, first feature matrices corresponding to the one-dimensional first attribute features included in the task to be assigned may also be first constructed, then one-dimensional second attribute features that are the same as the one-dimensional first attribute features in the task to be assigned may be found in the task processing group, and second feature matrices corresponding to the one-dimensional second attribute features may be constructed, and for one-dimensional first attribute features that do not have the same attribute features, the corresponding second feature matrices may all be set as zero matrices.

For example, in the application scenario described in step S201, when the task to be assigned includes A, B, C, D, E and F six one-dimensional first attribute features, and the task processing group S includes B, C, F, G, H, I and J seven one-dimensional second attribute features, a first feature matrix MeanFeature corresponding to the one-dimensional first attribute feature a may be first constructed_1AA first feature matrix MeanFeature corresponding to the one-dimensional first attribute feature B_1BA first feature matrix MeanFeature corresponding to the one-dimensional first attribute feature C_1CA first feature matrix MeanFeature corresponding to the one-dimensional first attribute feature D_1DA first feature matrix MeanFeature corresponding to the one-dimensional first attribute feature E_1EAnd a first feature matrix MeanFeature corresponding to the one-dimensional first attribute feature F_1FThen, when it is determined that the same attribute features B, C and F exist between the task to be distributed and the task processing group S, a second feature matrix MeanFeature corresponding to the one-dimensional second attribute feature B can be constructed_2BA second feature corresponding to the one-dimensional second attribute feature CFeature matrix MeanFeature_2CAnd a second feature matrix MeanFeature corresponding to the one-dimensional second attribute feature F_2FAnd setting the second feature matrixes corresponding to the one-dimensional attribute features A, D and E as zero matrixes, and finally setting the second feature matrixes according to MatchPoint_i＝MeanFeature_1i*(MeanFeature_2i)^TRespectively obtaining the similarity corresponding to the one-dimensional attribute characteristic A, the similarity corresponding to the one-dimensional attribute characteristic B, the similarity corresponding to the one-dimensional attribute characteristic C, the similarity corresponding to the one-dimensional attribute characteristic D, the similarity corresponding to the one-dimensional attribute characteristic E and the similarity corresponding to the one-dimensional attribute characteristic F.

Step S203, acquiring each first preset weight corresponding to each target one-dimensional first attribute feature;

in this case, because different attribute features often have different degrees of importance in task allocation, in the embodiment of the present invention, first preset weights corresponding to respective one-dimensional attribute features (which may include a one-dimensional first attribute feature and a one-dimensional second attribute feature) may be preset according to historical task allocation data, and the respective first preset weights and the corresponding one-dimensional attribute features may be stored in a preset database of the terminal device in an associated manner. Therefore, after determining each target one-dimensional first attribute feature and each target one-dimensional second attribute feature that are matched between the task to be assigned and the task processing group, where the target one-dimensional first attribute feature is one of the one-dimensional first attribute features, and the target one-dimensional second attribute feature is one of the one-dimensional second attribute features, the first preset weight corresponding to the target one-dimensional first attribute features may be found from the preset database, and if it is determined in the application scenario in step S201 that the number of the target one-dimensional first attribute features that are matched between the task to be assigned and the task processing group S is B, C, F, the first preset weight Q corresponding to the target one-dimensional first attribute feature B may be found from the preset database_BA first preset weight Q corresponding to the one-dimensional first attribute characteristic C of the target_CAnd a first preset weight Q corresponding to the one-dimensional first attribute feature F of the target_F。

Step S204, determining a matching value between the task to be distributed and the task processing group corresponding to the processing thread according to each first preset weight and each similarity.

It can be understood that after the first preset weights are obtained, the first preset weights and the corresponding similarities may be subjected to weighted summation to obtain a matching value between the task to be allocated and the task processing group corresponding to the processing thread, for example, in the above application scenario, the first preset weight Q may be used_B*Matchpoint_B+ a first predetermined weight Q_C*Matchpoint_C+ a first predetermined weight Q_F*Matchpoint_FThe obtained value is determined as a matching value between the task to be distributed and the task processing group S, so that the importance of each attribute feature is distinguished through weighting, and the accuracy of matching value calculation is improved.

Step S104, determining a first task processing group matched with the task to be distributed in the task processing groups according to the matching value, and sending the task to be distributed to a terminal corresponding to the first task processing group so as to instruct the terminal to process the task to be distributed.

In the embodiment of the present invention, after the matching values between the task to be allocated and each task processing group are obtained, a first task processing group in the task processing groups, which is matched with the task to be allocated, may be determined according to each matching value, for example, the task processing group with the largest matching value may be determined as the first task processing group matched with the task to be allocated, and the task to be allocated may be sent to the terminal corresponding to the first task processing group, so as to instruct the terminal to process the task to be allocated.

As shown in fig. 3, in a specific application scenario, the determining, according to the matching value, a first task processing group in the task processing groups, which matches the task to be allocated, may include:

s301, acquiring the maximum matching value in the matching values, and counting the number of the maximum matching values;

step S302, judging whether the number of the maximum matching values is more than 1;

step S303, when the number of the maximum matching values is 1, determining the task processing group corresponding to the maximum matching value as a first task processing group matched with the task to be distributed;

step S304, when the number of the maximum matching values is larger than 1, acquiring a preset one-dimensional second attribute feature in a task processing group corresponding to each maximum matching value, and acquiring a second preset weight corresponding to the preset one-dimensional second attribute feature, wherein the preset one-dimensional second attribute feature is an attribute feature shared between the task to be distributed and the corresponding task processing group;

step S305, determining a task processing group corresponding to a preset one-dimensional second attribute feature with the largest second preset weight as a first task processing group matched with the task to be distributed;

with regard to the above steps S301 to S305, the present scenario mainly determines the task processing group having the largest matching value as the first task processing group. Specifically, a maximum matching value of the matching values may be obtained, the number of the maximum matching values may be counted, and when the maximum matching value includes only one maximum matching value, the task processing group corresponding to the maximum matching value may be directly determined as a first task processing group matched with the task to be allocated; and when the maximum matching value includes a plurality of maximum matching values, acquiring a preset one-dimensional second attribute feature in the task processing group corresponding to each maximum matching value, and acquiring a second preset weight corresponding to the preset one-dimensional second attribute feature, where the preset one-dimensional second attribute feature is an attribute feature shared between the task to be allocated and the corresponding task processing group, and the second preset weight may be the first preset weight, so that the task processing group corresponding to the preset one-dimensional second attribute feature having the maximum second preset weight may be determined as the first task processing group matched with the task to be allocated.

For example, when the task to be assigned includes A, B, C, D, E and F one-dimensional first attribute features, the task processing group S includes B, F, G, H, I and J six one-dimensional second attribute features, the task processing group R includes A, C, I, J and L five one-dimensional second attribute features, and the task processing group Q includes A, F, K and L four one-dimensional second attribute features, and the matching value between the task to be assigned and the task processing group S is 80, the matching value between the task to be assigned and the task processing group R is 80, and the matching value between the task to be assigned and the task processing group Q is 60, then the one-dimensional second attribute features B and F in the task processing group S may be first obtained, the one-dimensional second attribute features a and C in the task processing group R may be obtained, and then the one-dimensional second attribute features a and C may be obtained respectively, B. C, F, and comparing the magnitudes of the second preset weights to obtain a one-dimensional second attribute feature with a maximum second preset weight, and if the obtained one-dimensional second attribute feature with the maximum second preset weight is a, determining the task processing group R corresponding to a as the first task processing group matched with the task to be distributed.

In this scenario, the processing level corresponding to each task processing group may be determined in advance from the history processing data of each task processing group, and for example, the processing level corresponding to each task processing group may be determined from the history processing time of each task processing group, where a task processing group with a shorter history processing time has a higher processing level and a task processing group with a longer history processing time has a lower processing level. Therefore, when the maximum matching values are two or more, the processing levels of the task processing groups corresponding to the maximum matching values can be obtained, so that the finally matched first task processing group can be determined according to the processing levels, for example, the task processing group with the highest processing level in the task processing groups corresponding to the maximum matching values can be determined as the first task processing group, so as to improve the task processing efficiency.

Further, in another specific application scenario, after the task to be allocated is allocated to the first task processing group, the method may further include:

step a, acquiring a task allocation condition of the first task processing group, and determining idle processing staff in the first task processing group according to the task allocation condition;

b, determining the task processing capacity of each idle processing staff according to the task processing record of each idle processing staff, and performing descending order arrangement on the idle processing staff according to the task processing capacity to obtain an arrangement group;

and c, selecting the idle processing staff with the first sequence in the arrangement group as target processing staff corresponding to the tasks to be distributed, and sending the tasks to be distributed to the terminals corresponding to the target processing staff so as to instruct the target processing staff to process the tasks to be distributed.

As for the above steps a to c, it can be understood that after the first task processing group corresponding to the task to be allocated is determined, the task allocation condition of the first task processing group may be obtained, for example, the backlog task amount of each processing employee in the first task processing group is obtained, so that the current state of each processing employee in the first task processing group may be determined according to the task allocation condition, and thus, the processing employee in an idle state is determined, that is, an idle processing employee without task processing at present is found out from the first task processing group, and when one idle employee is found, the task to be allocated may be directly sent to the terminal corresponding to the idle processing employee, so as to instruct the idle processing employee to process the task to be allocated.

When a plurality of idle processing employees are found, the task processing records of the idle processing employees can be obtained, so that the task processing capacity of the idle processing employees can be determined according to the task processing records, wherein the task processing capacity can be measured according to the task processing timeliness of the idle processing employees, and the shorter the task processing timeliness is, the stronger the corresponding task processing capacity is. After the task processing capacity of each idle processing employee is determined, each idle processing employee can be subjected to descending order arrangement according to the task processing capacity to obtain an arrangement number group of descending order arrangement (in the arrangement number group, the idle processing employee with the stronger task processing capacity is ranked more forward), the idle processing employee with the first order in the arrangement group is selected as the target processing employee corresponding to the task to be allocated, namely, the idle processing employee with the strongest task processing capacity in each idle processing employee is determined as the target processing employee corresponding to the task to be allocated, and the task to be allocated can be sent to the terminal corresponding to the target processing employee, so that the task allocation accuracy and the task allocation efficiency are improved.

Preferably, selecting the idle processing employee who is the first in the ranking group as the target processing employee corresponding to the task to be allocated, and sending the task to be allocated to the terminal corresponding to the target processing employee, may include:

step d, selecting the first idle processing staff in the arrangement group as the target processing staff corresponding to the tasks to be distributed, sending task distribution requests to the terminals corresponding to the target processing staff, and receiving reply information returned by the terminals;

step e, judging whether the reply information confirms to receive the task allocation request;

step f, when the reply information confirms that the task allocation request is received, the task to be allocated is sent to a terminal corresponding to the target processing staff;

and g, when the reply information is that the task allocation request is refused to be received, moving the idle processing staff currently ranked first in the ranking group to the last position of the ranking group, returning to execute the step of selecting the idle processing staff ranked first in the ranking group as the target processing staff corresponding to the task to be allocated, and sending the task allocation request to the terminal corresponding to the target processing staff, and the subsequent steps.

For the above steps d to g, it can be understood that after the target processing staff corresponding to the task to be allocated is determined, a task allocation request may be first sent to the terminal corresponding to the target processing staff, so as to determine whether the target processing staff can receive the task to be allocated according to the reply information of the target processing staff to the task allocation request, thereby ensuring the correctness and the validity of task allocation. When the reply information returned by the target processing staff indicates that the target processing staff confirms to receive the task allocation request, allocating the task to be allocated to the target processing staff; and when the reply message returned by the target processing employee indicates that the target processing employee is currently unable to receive the task allocation request, the next idle process employee from the set of ranked numbers may be selected to perform the task allocation operation, the first-ranked idle handler may be moved to the last position of the rank group to update the rank group, and the idle processing staff ranked first in the updated arrangement array can be reselected as the target processing staff corresponding to the task to be distributed, the sending of the task allocation request may then be resumed until there are idle processing staff receiving the task allocation request, the task allocation is timely and effectively performed by sending the task allocation request before allocation, so that the return re-allocation after allocation is avoided, and the allocation efficiency of the task allocation is improved.

In a possible implementation manner, the determining, according to the matching value, a first task processing group, which is matched with the task to be allocated, in the task processing group may include:

h, judging whether each matching value is smaller than a preset threshold value;

step i, if each matching value is smaller than the preset threshold value, respectively acquiring one-dimensional first attribute features in a matching feature library corresponding to each task processing group, wherein the one-dimensional first attribute features corresponding to the historical allocation tasks when the task processing group is determined to be the first task processing group matched with the historical allocation tasks are stored in the matching feature library corresponding to the task processing group;

step j, re-determining the matching value between the task to be distributed and each task processing group according to the one-dimensional first attribute feature in each matching feature library and the one-dimensional first attribute feature of the task to be distributed, and determining the first task processing group matched with the task to be distributed in the task processing group according to the re-determined matching value.

As for the above steps h to j, it can be understood that after each task allocation is completed, the one-dimensional first attribute feature of the completed allocation task (i.e. the historical allocation task in step i) may be stored in the matching feature library corresponding to the allocated first task processing group, and used as the auxiliary feature corresponding to the first task processing group, so as to indicate that the first task processing group may process the to-be-allocated tasks including the one-dimensional first attribute features, where the first task processing group is a specific task processing group. Therefore, when the next task to be assigned is assigned, the matching values between the task to be assigned and the task processing groups of the current time are calculated according to steps S101 to S104, and when the matching values between the task to be assigned and the task processing groups of the current time are all low, for example, all lower than the preset threshold (40%), and the first task processing group for processing the task to be assigned of the current time cannot be determined, the one-dimensional first attribute feature in the matching feature library corresponding to each task processing group is further obtained, and the matching value between each task processing group and the task to be assigned of the current time is re-determined according to the one-dimensional first attribute feature in each matching feature library and the one-dimensional first attribute feature of the task to be assigned of the current time, so that the first task processing group matching with the task to be assigned of the current time in the task processing group can be determined according to the re-determined matching values, and sending the task to be allocated to the terminal corresponding to the first task processing group to prompt the terminal to process the task to be allocated, and assisting to determine the first processing task group matched with the task to be allocated through the allocation record of the historical allocation task, so that the first task processing group is accurately determined, and the task to be allocated can be timely and effectively allocated to the task processing group for processing.

Further, after determining, according to the matching value, a first task processing group, which is matched with the task to be allocated, in the task processing groups, the method may include: and updating the one-dimensional first attribute characteristics in the corresponding matched characteristic library according to the matching value and the one-dimensional first attribute characteristics of the task to be distributed.

Specifically, when a task processing group corresponding to a certain subsequent matching feature library is determined to be a first task processing group for processing a new task to be allocated again, it may be determined whether a matching value between the first task processing group and the new task to be allocated is greater than a matching value between a task to be allocated and the task processing group corresponding to a one-dimensional first attribute feature stored in the matching feature library, and if so, the one-dimensional first attribute feature corresponding to the new task to be allocated may be used to refresh the one-dimensional first attribute feature stored in the matching feature library; if the attribute is less than the preset attribute, the matching feature library is not refreshed so as to keep the one-dimensional first attribute features stored in the matching feature library, and the one-dimensional first attribute features stored in the matching feature library are refreshed in real time so as to improve the correctness of the auxiliary features in the matching feature library, thereby improving the correctness and the effectiveness of task allocation.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

The above mainly describes a task assigning method, and a task assigning apparatus will be described in detail below.

Fig. 4 is a block diagram showing an embodiment of a task assigning apparatus according to an embodiment of the present invention. As shown in fig. 4, the task assigning apparatus includes:

a to-be-allocated task obtaining module 401, configured to obtain to-be-allocated tasks from a preset task queue according to a specified order;

a first attribute feature dimension reduction module 402, configured to determine a multi-dimensional first attribute feature corresponding to the task to be allocated, and perform dimension reduction processing on the multi-dimensional first attribute feature to obtain multiple one-dimensional first attribute features corresponding to the task to be allocated;

a second attribute feature dimension reduction module 403, configured to obtain a multi-dimensional second attribute feature corresponding to each preset task processing group, and perform dimension reduction processing on each multi-dimensional second attribute feature to obtain a plurality of one-dimensional second attribute features corresponding to each task processing group;

a matching value determining module 404, configured to determine a processing thread corresponding to each task processing group, analyze, by using the processing thread, the multiple one-dimensional first attribute features of the task to be allocated and the multiple one-dimensional second attribute features of the task processing group corresponding to the processing thread, and determine a matching value between the task to be allocated and each task processing group;

and the task allocation module 405 is configured to determine, according to the matching value, a first task processing group matched with the task to be allocated in the task processing groups, and send the task to be allocated to a terminal corresponding to the first task processing group, so as to instruct the terminal to process the task to be allocated.

Further, the matching value determining module 404 may include:

the feature matrix construction unit is used for determining each target one-dimensional first attribute feature and each target one-dimensional second attribute feature which are matched between the task to be distributed and the task processing group corresponding to the processing thread by adopting the processing thread, respectively constructing a first feature matrix of each target one-dimensional first attribute feature and constructing a second feature matrix of each target one-dimensional second attribute feature;

the similarity calculation unit is used for calculating the similarity between each first feature matrix and the corresponding second feature matrix;

the preset weight obtaining unit is used for obtaining each first preset weight corresponding to each target one-dimensional first attribute feature;

and the matching value determining unit is used for determining a matching value between the task to be distributed and the task processing group corresponding to the processing thread according to each first preset weight and each similarity.

Preferably, the similarity calculating unit is specifically configured to calculate the similarity between each first feature matrix and the corresponding second feature matrix according to the following formula:

Matchpoint_i＝MeanFeature_1i*(MeanFeature_2i)^T

Optionally, the second attribute feature dimension reduction module 403 may include:

and the second attribute feature extraction unit is used for extracting second attribute features of the processing staff in each task processing group and obtaining multi-dimensional second attribute features corresponding to each task processing group according to the extracted second attribute feature combinations.

Further, the task assigning module 405 may include:

the quantity counting unit is used for acquiring the maximum matching value in the matching values and counting the quantity of the maximum matching value;

a first determining unit, configured to determine, when the number of the maximum matching values is 1, a task processing group corresponding to the maximum matching value as a first task processing group matched with the task to be allocated;

acquiring preset attribute features, wherein the preset attribute features are used for acquiring preset one-dimensional second attribute features in a task processing group corresponding to each maximum matching value when the number of the maximum matching values is greater than 1, and acquiring second preset weights corresponding to the preset one-dimensional second attribute features, wherein the preset one-dimensional second attribute features are the attribute features shared between the tasks to be distributed and the corresponding task processing groups;

and the second determining unit is used for determining the task processing group corresponding to the preset one-dimensional second attribute feature with the maximum second preset weight as the first task processing group matched with the task to be distributed.

Preferably, the task allocation module 405 may include:

a matching value judging unit for judging whether each matching value is smaller than a preset threshold value;

a one-dimensional attribute feature obtaining unit, configured to obtain, if each of the matching values is smaller than the preset threshold, a one-dimensional first attribute feature in a matching feature library corresponding to each of the task processing groups, where the one-dimensional first attribute feature corresponding to the historical allocation task when the task processing group is determined to be a first task processing group matching the historical allocation task is stored in the matching feature library corresponding to the task processing group;

and the matching value re-determining unit is used for re-determining the matching value between the task to be distributed and each task processing group according to the one-dimensional first attribute feature in each matching feature library and the one-dimensional first attribute feature of the task to be distributed, and determining a first task processing group matched with the task to be distributed in the task processing groups according to the re-determined matching value.

Optionally, the task allocation module 405 may further include:

and the attribute feature updating unit is used for updating the one-dimensional first attribute features in the corresponding matching feature library according to the matching values and the one-dimensional first attribute features of the tasks to be distributed.

Fig. 5 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 5, the terminal device 5 of this embodiment includes: a processor 50, a memory 51, and computer readable instructions 52, such as a task allocation program, stored in the memory 51 and executable on the processor 50. The processor 50, when executing the computer readable instructions 52, implements the steps in the various embodiments of the task assignment method described above, such as the steps S101-S105 shown in fig. 1. Alternatively, the processor 50 executes the computer readable instructions 52 to implement the functions of the modules/units in the device embodiments, such as the modules 401 to 405 shown in fig. 4.

Illustratively, the computer readable instructions 52 may be partitioned into one or more modules/units that are stored in the memory 51 and executed by the processor 50 to implement the present invention. The one or more modules/units may be a series of computer-readable instruction segments capable of performing specific functions, which are used for describing the execution process of the computer-readable instructions 52 in the terminal device 5.

The terminal device 5 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor 50, a memory 51. Those skilled in the art will appreciate that fig. 5 is merely an example of a terminal device 5 and does not constitute a limitation of terminal device 5 and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the terminal device may also include input-output devices, network access devices, buses, etc.

The Processor 50 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 51 may be an internal storage unit of the terminal device 5, such as a hard disk or a memory of the terminal device 5. The memory 51 may also be an external storage device of the terminal device 5, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 5. Further, the memory 51 may also include both an internal storage unit and an external storage device of the terminal device 5. The memory 51 is used for storing the computer readable instructions and other programs and data required by the terminal device. The memory 51 may also be used to temporarily store data that has been output or is to be output.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A task allocation method, comprising:

2. The task allocation method according to claim 1, wherein the determining, by using the processing thread, the matching value between the task to be allocated and each of the task processing groups by analyzing the plurality of one-dimensional first attribute features of the task to be allocated and the plurality of one-dimensional second attribute features of the task processing groups corresponding to the processing thread, comprises:

determining each target one-dimensional first attribute characteristic and each target one-dimensional second attribute characteristic which are matched between the task to be distributed and the task processing group corresponding to the processing thread by using the processing thread, respectively constructing a first characteristic matrix of each target one-dimensional first attribute characteristic, and constructing a second characteristic matrix of each target one-dimensional second attribute characteristic;

calculating the similarity between each first feature matrix and the corresponding second feature matrix;

acquiring each first preset weight corresponding to each target one-dimensional first attribute feature;

and determining a matching value between the task to be distributed and the task processing group corresponding to the processing thread according to each first preset weight and each similarity.

3. The task allocation method according to claim 2, wherein the calculating the similarity between each first feature matrix and the corresponding second feature matrix comprises:

Matchpoint_i＝MeanFeature_1i*(MeanFeature_2i)^T

4. The task allocation method according to claim 1, wherein the obtaining of the multi-dimensional second attribute features corresponding to the preset task processing groups includes:

and extracting second attribute features of the processing staff in each task processing group, and combining the extracted second attribute features to obtain multi-dimensional second attribute features corresponding to each task processing group.

5. The task allocation method according to claim 1, wherein said determining a first task processing group of the task processing groups that matches the task to be allocated according to the matching value comprises:

acquiring the maximum matching value in the matching values, and counting the number of the maximum matching values;

when the number of the maximum matching values is 1, determining the task processing group corresponding to the maximum matching value as a first task processing group matched with the task to be distributed;

when the number of the maximum matching values is larger than 1, acquiring a preset one-dimensional second attribute feature in a task processing group corresponding to each maximum matching value, and acquiring a second preset weight corresponding to the preset one-dimensional second attribute feature, wherein the preset one-dimensional second attribute feature is an attribute feature shared between the task to be distributed and the corresponding task processing group;

and determining the task processing group corresponding to the preset one-dimensional second attribute feature with the maximum second preset weight as a first task processing group matched with the task to be distributed.

6. The task allocation method according to any one of claims 1 to 5, wherein the determining, according to the matching value, a first task processing group of the task processing groups that matches the task to be allocated includes:

judging whether each matching value is smaller than a preset threshold value;

if the matching values are smaller than the preset threshold value, respectively acquiring one-dimensional first attribute features in a matching feature library corresponding to each task processing group, wherein the one-dimensional first attribute features corresponding to the historical allocation tasks when the task processing groups are determined to be the first task processing groups matched with the historical allocation tasks are stored in the matching feature library corresponding to the task processing groups;

and re-determining the matching value between the task to be distributed and each task processing group according to the one-dimensional first attribute feature in each matching feature library and the one-dimensional first attribute feature of the task to be distributed, and determining a first task processing group matched with the task to be distributed in the task processing groups according to the re-determined matching value.

7. The task allocation method according to claim 6, wherein after determining a first task processing group matching the task to be allocated among the task processing groups according to the matching value, the method comprises:

and updating the one-dimensional first attribute characteristics in the corresponding matched characteristic library according to the matching value and the one-dimensional first attribute characteristics of the task to be distributed.

8. A task assigning apparatus, comprising:

9. A computer readable storage medium storing computer readable instructions, which when executed by a processor implement the steps of the task assignment method of any one of claims 1 to 7.

10. A terminal device comprising a memory, a processor, and computer readable instructions stored in the memory and executable on the processor, wherein the processor when executing the computer readable instructions performs the steps of: