CN111062572A

CN111062572A - Task allocation method and device

Info

Publication number: CN111062572A
Application number: CN201911135053.3A
Authority: CN
Inventors: 许笠; 张小彪; 王超
Original assignee: China Construction Bank Corp; CCB Finetech Co Ltd
Current assignee: China Construction Bank Corp
Priority date: 2019-11-19
Filing date: 2019-11-19
Publication date: 2020-04-24
Anticipated expiration: 2039-11-19
Also published as: CN111062572B

Abstract

The invention discloses a method and a device for task allocation, and relates to the technical field of computers. One embodiment of the method comprises: calculating the correlation degree of the task to be distributed and the task class in the task class set, and determining a first task class adapted to the task to be distributed; determining a first operator class in a set of operator classes adapted to the first task class; and allocating operators to the tasks to be allocated by determining the correlation between the tasks to be allocated and the historical tasks of the operators in the first operator class. The implementation mode solves the technical defects of subjectivity influence and contingency in the process of distributing the tasks to be distributed in the prior art, and further achieves the technical effect of distributing the tasks to be distributed to proper operators.

Description

Task allocation method and device

Technical Field

The invention relates to the technical field of computers, in particular to a method and a device for task allocation.

Background

When tasks to be distributed exist, in the prior art, operators are selected mostly by adopting a manual expert method or selecting operators by adopting a random method. The method adopting the artificial expert method mainly comprises the following steps: sequencing the operators according to the standard specified by the expert, and further determining the operator most suitable for the task to be distributed; the random method for selecting the operator is as follows: one of the operators who meet the task requirements is randomly selected to assign the task.

In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:

1. the manual expert method for selecting operators is based on the personal experience of experts to determine various capabilities required by task types, since there is no data support for historical tasks; moreover, the ability value of each operator given by the expert is not always accurate, if the task to be distributed relates to new ability, the index of the ability can only be scored by the expert, and the subjectivity is too strong.

2. The random approach is too fortuitous to guarantee that the proper operator is scheduled for the task to be assigned.

Disclosure of Invention

In view of this, embodiments of the present invention provide a method and an apparatus for task allocation, which can achieve the technical effect of allocating a task to be allocated to a relatively suitable operator.

To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a task allocation method including:

calculating the correlation degree of the task to be distributed and the task class in the task class set, and determining a first task class adapted to the task to be distributed;

determining a first operator class in a set of operator classes adapted to the first task class;

and allocating operators to the tasks to be allocated by determining the correlation between the tasks to be allocated and the historical tasks of the operators in the first operator class.

Optionally, determining a first operator class of the set of operator classes adapted to the first task class includes:

determining the correlation degree between the task class in the task class set and the operator in the operator class set;

and determining a first operator class in the operator class set adapted to the first task class according to the correlation.

Optionally, before determining the correlation between the task class in the task class set and the operator in the operator class set, the method includes:

classifying the historical tasks according to the attribute information of the historical tasks to obtain the task class;

and classifying the operators according to the attribute information of the operators to obtain operator classes.

Optionally, determining a degree of correlation between the task class in the task class set and the operator in the operator class set includes:

importing historical task information in a preset time period into a graph database to generate a historical task graph;

importing operator information in a preset time period into the graph database to generate an operator graph;

importing information of historical tasks executed by an operator in the preset time period into the graph database, and increasing a connecting line between the historical task graph and the operator graph;

and determining the correlation degree between the task class in the task class set and the operator in the operator class set according to the connecting line.

According to still another aspect of an embodiment of the present invention, there is provided an apparatus for task allocation, including:

the first task class determination module is used for calculating the correlation degree of the tasks to be distributed and the task classes in the task class set and determining the first task class adapted to the tasks to be distributed;

a first operator class determination module for determining a first operator class of a set of operator classes adapted to the first task class;

and the task allocation module is used for allocating the operators to the tasks to be allocated by determining the correlation between the tasks to be allocated and the historical tasks of the operators in the first operator class.

the task class obtaining module is used for classifying the historical tasks according to the attribute information of the historical tasks to obtain the task classes;

and the operator class obtaining module is used for classifying the operators according to the attribute information of the operators to obtain the operator classes.

According to another aspect of an embodiment of the present invention, there is provided a task assigning electronic device including:

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, the one or more processors implement the task assigning method provided by the present invention.

According to still another aspect of embodiments of the present invention, there is provided a computer-readable medium on which a computer program is stored, the program, when executed by a processor, implementing a task allocation method provided by the present invention.

One embodiment of the above invention has the following advantages or benefits:

according to the technical means for determining the similarity between the tasks to be distributed and the historical tasks, the technical defects that in the prior art, subjective influences exist and the tasks to be distributed have contingency are overcome, and therefore the technical effect that the tasks to be distributed are distributed to proper operators is achieved.

Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.

Drawings

The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:

FIG. 1 is a schematic diagram of a main flow of a method of task assignment according to an embodiment of the present invention;

FIG. 2 is a schematic diagram illustrating a detailed step flow of a method of task assignment according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of the major modules of a task assignment device according to an embodiment of the present invention;

FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;

fig. 5 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.

Detailed Description

Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

Fig. 1 is a schematic diagram of a main flow of a task allocation method according to an embodiment of the present invention, as shown in fig. 1,

step S101, calculating the correlation degree of a task to be distributed and a task class in a task class set, and determining a first task class adapted to the task to be distributed;

step S102, determining a first operator class in the operator class set adapted to the first task class;

step S103, allocating operators to the tasks to be allocated by determining the correlation between the tasks to be allocated and the historical tasks of the operators in the first operator class.

The task class refers to the type of the task; the task class set refers to a set formed by a plurality of task classes; similarly, the operator class refers to the type of the operator; the operator class set refers to a set composed of a plurality of operator classes.

The task class can classify the historical tasks according to attribute information of the historical tasks, and then the task class is obtained; the attribute information of the historical task may include, but is not limited to, one of: role, authority, affiliation, capability requirements on the operator, etc.

The operator class can classify the operators according to the attribute information of the operators, and then the operator class is obtained; the attribute information of the operator may include, but is not limited to, one of: role, authority, affiliation, capability, etc.

When a task to be allocated exists, the type of the task to be allocated may not be known to a person who allocates the task, and the task class most similar to the task to be allocated can be determined by calculating the correlation degree between the task to be allocated and the task class in the determined task class set, that is, the type of the task to be allocated can be set as the most similar task class, and for convenience of subsequent description, the most similar task class is referred to as a first task class.

Wherein determining a first operator class in the set of operator classes adapted to the first task class is preceded by:

determining the correlation degree between the task class in the task class set and the operator in the operator class set; thereby facilitating direct access to the first operator adapted to the first task class. Wherein statistics may be employed to account for historical tasks performed by the operator. The representation of the correlation includes, but is not limited to, graphical representation and tabular representation.

In an alternative embodiment of the present application, determining a correlation between a task class in the set of task classes and an operator in the set of operator classes includes:

Before the tasks to be distributed are distributed, the technical means of establishing a historical task graph and an operator graph based on historical tasks and calculating the correlation relationship between each historical task in the historical task graph and each operator in the operator graph is included, so that the correlation degree in the tasks to be distributed can be determined more accurately and more efficiently when the operators are distributed to the tasks to be distributed subsequently.

step S201, importing historical task information in a preset time period into a graph database, generating a historical task graph, and classifying the historical tasks according to attribute information of the historical tasks;

step S202, importing operator information in a preset time period into the graph database to generate an operator graph, and classifying the operators according to the attribute information of the operators;

step S203, importing information of historical tasks executed by an operator in the preset time period into the graph database, and increasing a connecting line between the historical task graph and the operator graph;

step S204, calculating the correlation between the task classes and the operator classes according to the connection condition, and finding out the most relevant operator class of each task class;

step S205, for the task to be distributed, calculating the correlation degree between the task to be distributed and the task class in the task class set, and determining a first task class adapted to the task to be distributed;

step S206, determining a first operator class in the operator class set adapted to the first task class according to the result of the step S204;

step S207, allocating operators to the tasks to be allocated by determining the correlation between the tasks to be allocated and the historical tasks of the operators in the first operator class.

Fig. 3 is a schematic diagram of main modules of a task allocation apparatus 300 according to an embodiment of the present invention, as shown in fig. 3, including:

the first task class determining module 301 is configured to calculate a correlation between a task to be allocated and a task class in a task class set, and determine a first task class to which the task to be allocated is adapted;

a first operator class determination module 302, configured to determine a first operator class in the operator class set adapted to the first task class;

and the task allocation module 303 is configured to allocate the operator to the task to be allocated by determining a correlation between the task to be allocated and the historical task of the operator in the first operator class.

Fig. 4 shows an exemplary system architecture 400 to which the task allocation method or the task allocation apparatus of the embodiments of the present invention can be applied.

As shown in fig. 4, the system architecture 400 may include

terminal devices

401, 402, 403, a network 404, and a server 405. The network 404 serves as a medium for providing communication links between the

terminal devices

401, 402, 403 and the server 405. Network 404 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.

A user may use

terminal devices

401, 402, 403 to interact with a server 405 over a network 404 to receive or send messages or the like. The

terminal devices

401, 402, 403 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).

The

terminal devices

401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The server 405 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the

terminal devices

401, 402, 403. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.

It should be noted that the task allocation method provided by the embodiment of the present invention is generally executed by the server 405, and accordingly, the task allocation apparatus is generally disposed in the server 405.

It should be understood that the number of terminal devices, networks, and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

Referring now to FIG. 5, shown is a block diagram of a computer system 500 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 5, the computer system 500 includes a central processing module (CPU)501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.

The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.

In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program performs the above-described functions defined in the system of the present invention when executed by the central processing module (CPU) 501.

It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a sending module, an obtaining module, a determining module, and a first processing module. The names of these modules do not form a limitation on the modules themselves in some cases, and for example, the sending module may also be described as a "module sending a picture acquisition request to a connected server".

As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise:

According to the technical scheme of the embodiment of the invention, the following beneficial effects can be achieved:

The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method of task allocation, comprising:

2. The method of claim 1, wherein determining a first operator class of a set of operator classes adapted to the first task class comprises:

3. The method of claim 2, wherein prior to determining the relevance between the task class in the set of task classes and the operator in the set of operator classes, comprising:

4. The method of claim 2, wherein determining a degree of correlation between a task class in the set of task classes and an operator in the set of operator classes comprises:

5. An apparatus for task assignment, comprising:

6. The apparatus of claim 5, wherein determining a first operator class of the set of operator classes adapted to the first task class comprises:

7. The apparatus of claim 6, wherein prior to determining the relevance between the task class in the set of task classes and the operator in the set of operator classes, comprising:

8. The apparatus of claim 6, wherein determining a degree of correlation between a task class in the set of task classes and an operator in the set of operator classes comprises:

9. An electronic device for task assignment, comprising:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.

10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-4.