WO2021042510A1 - Task allocation method and apparatus, readable storage medium and terminal device - Google Patents

Task allocation method and apparatus, readable storage medium and terminal device Download PDF

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Publication number
WO2021042510A1
WO2021042510A1 PCT/CN2019/116633 CN2019116633W WO2021042510A1 WO 2021042510 A1 WO2021042510 A1 WO 2021042510A1 CN 2019116633 W CN2019116633 W CN 2019116633W WO 2021042510 A1 WO2021042510 A1 WO 2021042510A1
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task
employee
attribute
assigned
data
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PCT/CN2019/116633
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French (fr)
Chinese (zh)
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王培强
李亮
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平安科技(深圳)有限公司
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0631Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311Scheduling, planning or task assignment for a person or group
    • G06Q10/063112Skill-based matching of a person or a group to a task
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/243Classification techniques relating to the number of classes
    • G06F18/24323Tree-organised classifiers

Definitions

  • This application relates to the field of data processing technology, and in particular to a task allocation method, device, computer-readable storage medium, and terminal equipment.
  • the assignment is often directly based on the task or job type, that is, only according to the corresponding relationship between the task or job type and the employee, and when the type of a certain task or job is determined not
  • this simple way of assigning tasks based on the corresponding relationship between tasks or job types and employees is likely to cause task assignment errors or unreasonable task assignments, which greatly affects the efficiency of task assignment.
  • the embodiments of the present application provide a task allocation method, device, computer-readable storage medium, and terminal equipment, which can perform reasonable and accurate task allocation, and improve the efficiency and rationality of task allocation.
  • the first aspect of the embodiments of the present application provides a task allocation method, including:
  • Each of the first attribute characteristics is input to a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model is based on the attribute A model with features as nodes and task levels as decision-making results;
  • a corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be assigned is sent to a terminal corresponding to the target employee to prompt the target employee to process the task to be assigned.
  • a task allocation device including:
  • the attribute feature obtaining module is used to obtain each first attribute feature corresponding to the task to be assigned;
  • the task level determination module is configured to input each of the first attribute characteristics into a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model
  • the decision tree model is a model with attribute features as nodes and task levels as decision results
  • the candidate employee group determining module is used to determine the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
  • the task assignment module is used to select the corresponding target employee from the candidate employee group based on a preset selection method, and send the task to be assigned to the terminal corresponding to the target employee to prompt the target employee to Tasks to be assigned for processing.
  • the third aspect of the embodiments of the present application provides a computer-readable storage medium, the computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the foregoing first aspect is implemented. Describe the steps of the task allocation method.
  • a terminal device including a memory, a processor, and computer-readable instructions stored in the memory and running on the processor, and the processor executes the The following steps are implemented when computer readable instructions are:
  • Each of the first attribute characteristics is input to a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model is based on the attribute A model with features as nodes and task levels as decision-making results;
  • a corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be assigned is sent to a terminal corresponding to the target employee to prompt the target employee to process the task to be assigned.
  • each first attribute feature corresponding to the task to be assigned can be obtained, and then each first attribute feature can be input to the preset decision tree model to obtain the first attribute feature corresponding to the task to be assigned
  • a task level the candidate employee group corresponding to the first task level can be determined according to the preset correspondence relationship, and the corresponding target employee can be selected from the candidate employee group based on the preset selection method to automatically assign the tasks to be assigned, so as to pass
  • the preset decision tree model performs a comprehensive analysis of the first attribute characteristics of the tasks to be assigned to accurately determine the task level of the task to be assigned, so that a reasonable and accurate task assignment can be carried out according to the task level, so as to realize the automation and standardization of task assignment and reduce tasks
  • the labor cost in the distribution improves the efficiency and rationality of task distribution.
  • FIG. 1 is a flowchart of an embodiment of a task allocation method in an embodiment of this application
  • FIG. 2 is a schematic flowchart of a task allocation method in an application scenario for constructing a preset decision tree model in an embodiment of the application;
  • FIG. 3 is a schematic diagram of a process of task allocation in an application scenario of a task allocation method in an embodiment of the application;
  • FIG. 4 is a schematic flowchart of a task allocation method in an embodiment of the application for task allocation in another application scenario
  • FIG. 5 is a structural diagram of an embodiment of a task distribution device in an embodiment of the application.
  • Fig. 6 is a schematic diagram of a terminal device provided by an embodiment of the application.
  • the embodiments of the present application provide a task allocation method, device, computer-readable storage medium, and terminal equipment, which are used to perform reasonable and accurate task allocation and improve task allocation efficiency and rationality.
  • an embodiment of the present application provides a task allocation method, and the task allocation method includes:
  • Step S101 Obtain each first attribute feature corresponding to the task to be assigned
  • the execution subject of the embodiments of the present application is a terminal device, and the terminal device includes, but is not limited to, computing devices such as desktop computers, notebooks, palmtop computers, and cloud servers.
  • the user can upload or send the task to be allocated to the terminal device, where the uploaded or sent task to be allocated may include the introduction content of the task to be allocated, etc.
  • the terminal device receives the task to be assigned, it can obtain each first attribute feature corresponding to the task to be assigned from the corresponding introduction content, for example, a corresponding key can be set for each first attribute feature in advance Words, the terminal device can obtain each first attribute feature by performing a keyword search on the introduction content.
  • the sales list can be stored in the form of an Excel file, where the sales list can be a list of people who are likely to purchase related products or services, and can be stored
  • the Excel file containing the sales list is uploaded or sent to the terminal device, and the terminal device can extract the first attribute characteristics such as the category, region, source, age, and occupation corresponding to the sales list from the Excel file.
  • Step S102 Input each of the first attribute characteristics into a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model It is a model that takes attribute characteristics as nodes and task level as decision-making results;
  • the terminal device can input each first attribute feature into a preset decision tree model, and the preset decision tree model is Each attribute feature is a node, and the corresponding task level is a model of the decision result.
  • the preset decision tree model can match each first attribute feature with each node in the decision tree to determine the to-be-assigned The first task level corresponding to the task.
  • the first task level is used to indicate the task quality of the task to be allocated, wherein the task quality can be determined based on the predicted allocation result corresponding to the task to be allocated, and the predicted allocation result refers to the predicted allocation result.
  • the distribution success rate (or sales success rate) of the tasks to be allocated can evaluate the task quality of the sales list based on the predicted sales results of the sales list, so as to construct the first task level corresponding to the sales list.
  • the first task level corresponding to the sales list whose predicted sales result (such as the predicted sales success rate) is higher than 90% can be determined as the excellent level, indicating that the quality of the sales list is very good; the predicted sales result can be located at 75%
  • the first task level corresponding to the sales list between 90% and 90% is determined as the good level, indicating that the quality of the sales list is good; the first task level corresponding to the sales list with the predicted sales result between 60% and 75% can be determined.
  • the task level is determined to be medium, which means that the quality of the sales list is average; and the first task level corresponding to the sales list whose predicted sales result is less than 60% can be determined as the poor level, which means that the quality of the sales list is poor, etc. Wait.
  • the preset decision tree model is constructed through the following steps:
  • Step S201 Obtain a preset number of historical distribution data, where the historical distribution data includes second attribute characteristics and second distribution results corresponding to each historical task;
  • Step S202 Determine the attribute weight corresponding to each of the second attribute characteristics according to each of the second assignment results, and determine the second assignment corresponding to each of the historical tasks according to each of the attribute weights and each of the second assignment results grade;
  • the historical distribution data when constructing the preset decision tree model, may be obtained first, and each obtained historical distribution data may include the second attribute feature and the second distribution result corresponding to each historical task.
  • the second allocation result may include allocation success and allocation failure; secondly, big data analysis can be performed on all the second allocation results to determine the allocation success rate of the historical task corresponding to each of the second attribute characteristics, and Determine the attribute weight corresponding to each of the second attribute features according to the distribution success rate of each of the second attribute features.
  • big data analysis can be performed on all the second assignment results to determine the second attribute feature (such as the source)
  • the allocation success rate of you can get the number of historical tasks that contain the second attribute feature (source) and have been successfully allocated, and combine this number/the total number of historical tasks to obtain the second attribute feature (source) )
  • Distribution success rate the higher the distribution success rate, the greater the attribute weight corresponding to the second attribute feature (source), on the contrary, the lower the distribution success rate, the higher the attribute weight corresponding to the second attribute feature (source) small.
  • the second task level corresponding to each historical task can be obtained according to the attribute weight corresponding to the second attribute feature, for example, according to:
  • the final allocation success rate represents the task quality of the historical task, therefore, the second allocation success rate of each historical task can be determined according to the corresponding final allocation success rate.
  • the task level is to accurately analyze the task level of each historical task by comprehensively considering multiple attribute features and attribute weights corresponding to multiple attribute features to ensure the rationality and effectiveness of the task level determination.
  • SuccRate r is the rth history
  • the final allocation success rate corresponding to the task FeaValue rt is the allocation success rate corresponding to the t-th second attribute feature of the r-th historical task
  • Weight rt is the attribute corresponding to the t-th second attribute feature of the r-th historical task
  • Quotiety r is the weighting coefficient corresponding to the rth historical task.
  • Step S203 Calculate the information gain of each of the second attribute features based on each of the attribute weights and each of the second task levels, and construct the nodes of the decision tree according to each of the information gains and each of the second attribute features ;
  • Step S204 Construct the preset decision tree model according to the constructed node and each of the second task levels.
  • the calculating the information gain of each second attribute feature based on each of the attribute weights and each of the second task levels may include:
  • S is a data set composed of historical distribution data
  • n is the total number of second task levels included in the data set
  • p i is the proportion of the i-th second task level in the data set
  • Gain(S,d) is the information gain of the second attribute feature d
  • m is the number of data subsets obtained by dividing the data set according to the second attribute feature d
  • is the number of data in the data set
  • is the number of data in the jth data subset
  • Wegiht(d) is the attribute weight corresponding to the second attribute feature d.
  • the non-leaf node of each level of the decision tree can be constructed according to the information gain of each second attribute feature, where the greater the information gain, the node corresponding to the second attribute feature corresponding to the information gain in the decision tree
  • Level is not a leaf node, and the decision result corresponding to each leaf node in the constructed decision tree can be determined according to the second task level corresponding to each historical assignment task.
  • each non-leaf node is a second attribute feature
  • the connection between nodes can be the judgment condition that the upper level node to the next level node needs to meet
  • each leaf node is a decision result
  • the decision result is the second task level corresponding to all the judgment conditions from the root node to the leaf node.
  • the decision tree After the decision tree with the second attribute feature as the node and the second task level as the decision result is obtained, the decision tree can be determined as the preset decision tree model, which can be accurately determined through the calculation of attribute entropy and information gain The node position of each attribute feature in the decision tree and the judgment conditions in the decision-making process are accurately determined to ensure the accuracy of the construction of the preset decision tree model, thereby improving the accuracy of the task level determination in the task to be assigned.
  • the attribute weight of each attribute feature is determined by performing big data analysis on a large amount of historical distribution data, and the information gain of each historical distribution data is obtained by calculation, so as to accurately determine the decision-making of each attribute feature according to the information gain and attribute weight
  • the position of the node in the tree can ensure the accuracy of the construction of the preset decision tree model, thereby improving the accuracy of task level determination in the subsequent tasks to be assigned.
  • the assignment data (including the first assignment result and each first attribute characteristic) corresponding to the task to be assigned can be used as the data Samples are used to update the selected historical distribution data in the decision tree to update the decision tree according to the updated historical distribution data, that is, through real-time updating and increasing the data samples in the decision tree construction, the task level determination is more reasonable and more accurate The preset decision tree model.
  • Step S103 Determine the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
  • a preset correspondence relationship between task levels and employee groups can also be set in advance, wherein the number of groups of employee groups is the same as the number of levels of task levels, and the employee groups can be divided according to the work ability of each employee, etc.
  • each employee can be scored according to their work ability, etc., and each employee can be divided into groups according to the score interval in which the score is located, and multiple employee groups can be obtained.
  • the score can be placed in the first score interval (such as 90 The employees with scores above) are divided into the first employee group, the employees whose scores are in the second score range (such as 80 to 90 points) are divided into the second employee group, and the scores are in the third score range (such as 70 to 80 points).
  • the preset corresponding relationship between the preset task level and the employee group can be: the first employee group corresponds to the excellent level, the second employee group corresponds to the good level, the third employee group corresponds to the middle level, and the second employee group corresponds to the good level.
  • the four employee groups correspond to the difference level.
  • the first task level corresponding to the task to be assigned is determined by using the preset decision tree model, and the first task level is a specific level of the task levels, it can be determined according to the preset decision tree model. It is assumed that the corresponding relationship determines the candidate employee group corresponding to the first task level, where the candidate employee group is a specific employee group in the employee group. For example, when it is determined that the first task level corresponding to the task to be assigned is an excellent level, it can be determined that the corresponding candidate employee group is the first employee group; and when it is determined that the first task level corresponding to the task to be assigned is medium When leveling, it can be determined that the corresponding candidate employee group is the third employee group, and so on.
  • Step S104 Select a corresponding target employee from the candidate employee group based on a preset selection method, and send the task to be assigned to the terminal corresponding to the target employee to prompt the target employee to respond to the task to be assigned To process.
  • the target employee can be determined from the candidate employee group for automatic task assignment.
  • the preset selection method corresponding to each employee group can be set in advance, so that the target employee can be selected from the employee group through the preset selection method corresponding to the employee group.
  • the default selection method corresponding to the first group of employees can be set to random selection
  • the default selection method corresponding to the second group of employees can be set to the selection method based on processing capabilities (that is, the more capable employees are, the easier it is.
  • the default selection method corresponding to the third employee group can be set to the selection method based on the backlog amount of tasks (that is, the lesser the backlog amount of tasks, the easier it is to be selected), and so on. Therefore, after the candidate employee group corresponding to the task to be assigned is determined, the preset selection method corresponding to the candidate employee group can be obtained, so that the corresponding target can be selected from the candidate employee group based on the preset selection method Employees, and can automatically send the task to be assigned to the terminal corresponding to the selected target employee to prompt the target employee to process the task to be assigned.
  • the same preset selection method can be set for all employee groups.
  • the preset selection methods of all employee groups can be set to a selection method based on processing capabilities and backlog tasks. Therefore, as shown in FIG. 3, selecting a corresponding target employee from the candidate employee group based on a preset selection method, and sending the task to be assigned to a terminal corresponding to the target employee, may include:
  • Step S301 Obtain the task status of the candidate employee group, and determine the idle employees in the candidate employee group according to the task status;
  • Step S302 Determine the task processing ability of each idle employee according to the allocation record of each idle employee, and sort the idle employees in descending order according to the task processing ability to obtain a permutation array;
  • Step S303 The idle employee ranked first in the arrangement array is selected as the target employee corresponding to the task to be assigned, and the task to be assigned is sent to the terminal corresponding to the target employee.
  • the task status of the candidate employee group can be obtained, such as obtaining the backlog of each employee in the candidate employee group Task quantity, etc., so that the current task status of each employee in the candidate employee group can be determined according to the task status, so as to determine the employees whose task status is idle, that is, to find out from the candidate employee group that there is currently no task processing If there is only one idle employee found, the task to be assigned can be directly sent to the terminal corresponding to the idle employee.
  • the allocation record of each idle employee can be obtained, that is, the task processing record of the historical task that each idle employee has processed, so as to determine each idle employee according to the task record of each historical task.
  • the task processing ability of employees can be measured by the task processing success rate of each idle employee. The higher the task processing success rate, the stronger the corresponding task processing ability.
  • the idle employees can be sorted in descending order according to the task processing ability, and a descending array is obtained.
  • the idle employees with the stronger task processing ability are sorted more reliably Before, the first idle employee in the array is selected as the target employee corresponding to the task to be assigned, that is, the idle employee with the strongest task processing ability among the idle employees is determined as the target employee corresponding to the task to be assigned , And the task to be allocated can be sent to the terminal corresponding to the target employee to improve the accuracy and efficiency of task allocation.
  • the first idle employee in the arrangement array is selected as the target employee corresponding to the task to be assigned, and the task to be assigned is sent to the target employee corresponding to the target employee.
  • the terminal can include:
  • Step S401 Select the first idle employee in the arrangement array as the target employee corresponding to the task to be assigned, send a task assignment request to the terminal corresponding to the target employee, and receive reply information returned by the terminal;
  • Step S402 Determine whether the reply message is to confirm the reception of the task to be assigned
  • Step S403 When the reply message is to confirm receipt of the task to be assigned, the task to be assigned is sent to the terminal corresponding to the target employee;
  • Step S404 When the reply message is to refuse to receive the task to be assigned, move the idle employee ranked first to the end of the permutation array to update the permutation array, and return to execute the permutation
  • the first-ranked idle employee in the array is selected as the target employee corresponding to the task to be assigned, and the steps and subsequent steps of sending a task assignment request to the terminal corresponding to the target employee.
  • the task assignment request may be first sent to the terminal corresponding to the target employee, so as to pass the target employee to the target employee.
  • the reply information of the task assignment request is used to determine whether the target employee can receive the task to be assigned, so as to ensure the correctness and effectiveness of the task assignment.
  • the task to be assigned is sent to the terminal corresponding to the target employee; and when the target employee returns the reply information
  • the next idle employee can be selected from the permutation array to perform the task assignment operation, and the idle employee with the first ranking can be moved to the permutation array
  • the task allocation can be performed in a timely and effective manner by sending the task allocation request before the task allocation, so as to avoid the return and redistribution after the allocation, so as to improve the task allocation efficiency.
  • each first attribute feature corresponding to the task to be assigned can be obtained, and then each first attribute feature can be input into the preset decision tree model to obtain the first attribute feature corresponding to the task to be assigned
  • a task level the candidate employee group corresponding to the first task level can be determined according to the preset corresponding relationship, and the corresponding target employee can be selected from the candidate employee group based on the preset selection method to automatically assign the tasks to be assigned, so as to pass
  • the preset decision tree model performs a comprehensive analysis of the attributes and characteristics of the tasks to be assigned to accurately determine the task level of the task to be assigned, so that reasonable and accurate task assignment can be carried out according to the task level, so as to realize the automation and standardization of task assignment, and reduce the task distribution
  • the labor cost is improved, and the task allocation efficiency and the rationality of the allocation are improved.
  • a task distribution method is mainly described above, and a task distribution device will be described in detail below.
  • an embodiment of the present application provides a task allocation device, and the task allocation device includes:
  • the attribute feature acquiring module 501 is configured to acquire each first attribute feature corresponding to the task to be assigned;
  • the task level determination module 502 is configured to input each of the first attribute characteristics into a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, where the The preset decision tree model is a model that takes attribute features as nodes and task levels as decision results;
  • the candidate employee group determining module 503 is configured to determine the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
  • the task allocation module 504 is configured to select a corresponding target employee from the candidate employee group based on a preset selection method, and send the task to be assigned to the terminal corresponding to the target employee to prompt the target employee to The tasks to be assigned are processed.
  • the task distribution device may further include:
  • the historical allocation data acquisition module is configured to acquire a preset number of historical allocation data, where the historical allocation data includes the second attribute characteristics and second allocation results corresponding to each historical task;
  • the attribute weight determination module is configured to determine the attribute weight corresponding to each of the second attribute characteristics according to each of the second assignment results, and determine the corresponding historical task according to each of the attribute weights and each of the second assignment results The second task level;
  • the information gain calculation module is configured to calculate the information gain of each of the second attribute features based on each of the attribute weights and each of the second task levels, and make a decision based on each of the information gains and each of the second attribute features Node construction of the tree;
  • the decision tree model construction module is used to construct the preset decision tree model according to the constructed node and each of the second task levels.
  • the information gain calculation module may include:
  • the attribute entropy calculation unit is configured to calculate the attribute entropy Entropy(S) of the data set formed by the historical distribution data according to the following formula:
  • S is a data set composed of historical distribution data
  • n is the total number of second task levels included in the data set
  • p i is the proportion of the i-th second task level in the data set
  • the information gain calculation unit is configured to calculate the information gain of each second attribute feature according to the attribute entropy and the attribute weight according to the following formula:
  • Gain(S,d) is the information gain of the second attribute feature d
  • m is the number of data subsets obtained by dividing the data set according to the second attribute feature d
  • is the number of data in the data set
  • is the number of data in the jth data subset
  • Wegiht(d) is the attribute weight corresponding to the second attribute feature d.
  • the task distribution device may further include:
  • the model update module is used to obtain the first allocation result corresponding to the task to be allocated, and to update the historical allocation data based on the first allocation result corresponding to the task to be allocated and the first attribute feature, so as to update the historical allocation data according to the updated task. Update the preset decision tree model with the historical distribution data of.
  • the task allocation module 504 may include:
  • An idle employee determining unit configured to obtain the task status of the candidate employee group, and determine the idle employees in the candidate employee group according to the task status;
  • the permutation array acquisition unit is used to determine the task processing capability of each idle employee according to the allocation record of each idle employee, and arrange the idle employees in descending order according to the task processing capability to obtain the permutation array;
  • the task allocation unit is configured to select the idle employee ranked first in the arrangement array as the target employee corresponding to the task to be allocated, and send the task to be allocated to the terminal corresponding to the target employee.
  • the task allocation unit may include:
  • the allocation request sending sub-unit is used to select the first idle employee in the arrangement array as the target employee corresponding to the task to be allocated, send a task allocation request to the terminal corresponding to the target employee, and receive the terminal Reply information returned;
  • the task allocation sub-unit is configured to send the task to be allocated to the terminal corresponding to the target employee when the reply message is to confirm receipt of the task to be allocated;
  • the permutation array update unit is used for when the reply message is to refuse to receive the task to be assigned, move the first-ranked idle employee to the last position of the permutation array to update the permutation array and return to execution
  • the first-ranked idle employee in the arrangement array is selected as the target employee corresponding to the task to be assigned, and the step of sending a task assignment request to the terminal corresponding to the target employee and subsequent steps.
  • Fig. 6 is a schematic diagram of a terminal device provided by an embodiment of the present application.
  • the terminal device 6 of this embodiment includes: a processor 60, a memory 61, and computer-readable instructions 62 stored in the memory 61 and running on the processor 60, such as a task allocation program .
  • the processor 60 executes the computer-readable instructions 62
  • the steps in the foregoing task allocation method embodiments are implemented, for example, steps S101 to S104 shown in FIG. 1.
  • the processor 60 executes the computer-readable instructions 62
  • the functions of the modules/units in the foregoing device embodiments such as the functions of the modules 501 to 504 shown in FIG. 5, are implemented.
  • the computer-readable instructions 62 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 61 and executed by the processor 60, To complete this application.
  • the one or more modules/units may be a series of computer-readable instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer-readable instructions 62 in the terminal device 6.
  • the terminal device 6 may be a computing device such as a desktop computer, a notebook, a palmtop computer, and a cloud server.
  • the terminal device may include, but is not limited to, a processor 60 and a memory 61.
  • FIG. 6 is only an example of the terminal device 6 and does not constitute a limitation on the terminal device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components.
  • the terminal device may also include input and output devices, network access devices, buses, and the like.
  • the processor 60 may be a central processing unit (Central Processing Unit, CPU), other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (ASIC), Ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc.
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
  • the memory 61 may be an internal storage unit of the terminal device 6, such as a hard disk or a memory of the terminal device 6.
  • the memory 61 may also be an external storage device of the terminal device 6, such as a plug-in hard disk equipped on the terminal device 6, a smart memory card (Smart Media Card, SMC), and a Secure Digital (SD) Card, Flash Card, etc. Further, the memory 61 may also include both an internal storage unit of the terminal device 6 and an external storage device.
  • the memory 61 is used to store the computer-readable instructions and other programs and data required by the terminal device.
  • the memory 61 can also be used to temporarily store data that has been output or will be output.
  • the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
  • Non-volatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory may include random access memory (RAM) or external cache memory.
  • RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Channel (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

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Abstract

A task allocation method and apparatus, a storage medium and a terminal device. The task allocation method comprises: obtaining each first attribute feature corresponding to a task to be allocated (S101); inputting each first attribute feature into a preset decision tree model to obtain a first task level corresponding to the task to be allocated output by the preset decision tree model, wherein the preset decision tree model is a model using attribute features as nodes and task levels as decision results (S102); determining a candidate employee group corresponding to the first task level according to preset correspondences between the task levels and employee groups (S103); and selecting a corresponding target employee from the candidate employee group on the basis of a preset selection mode, and sending the task to be allocated to a terminal corresponding to the target employee (S104), so as to comprehensively analyze each first attribute feature of said task by means of the preset decision tree model to accurately determine the task level of the said task, thereby performing reasonable and accurate task allocation according to the task level.

Description

一种任务分配方法、装置、可读存储介质及终端设备Task distribution method, device, readable storage medium and terminal equipment
本申请要求于2019年09月02日提交中国专利局、申请号为201910824906.8、发明名称为“一种任务分配方法、装置、可读存储介质及终端设备”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。This application claims the priority of a Chinese patent application filed with the Chinese Patent Office, the application number is 201910824906.8, and the invention title is "a task distribution method, device, readable storage medium and terminal equipment" on September 2, 2019. All of them The content is incorporated in this application by reference.
技术领域Technical field
本申请涉及数据处理技术领域,尤其涉及一种任务分配方法、装置、计算机可读存储介质及终端设备。This application relates to the field of data processing technology, and in particular to a task allocation method, device, computer-readable storage medium, and terminal equipment.
背景技术Background technique
目前任务或者作业的分配方法中,往往是直接根据任务或者作业类型来进行分配,即仅根据任务或者作业类型与员工之间的对应关系来进行分配,而当某一任务或者作业的类型确定不准确或者不合理时,这种简单根据任务或者作业类型与员工之间的对应关系来进行任务分配的方式容易造成任务分配错误或者造成任务分配的不合理,极大地影响任务分配效率。In the current task or job assignment method, the assignment is often directly based on the task or job type, that is, only according to the corresponding relationship between the task or job type and the employee, and when the type of a certain task or job is determined not When accurate or unreasonable, this simple way of assigning tasks based on the corresponding relationship between tasks or job types and employees is likely to cause task assignment errors or unreasonable task assignments, which greatly affects the efficiency of task assignment.
综上,如何提高任务的分配效率和合理性成为本领域技术人员亟待解决的问题。In summary, how to improve the efficiency and rationality of task allocation has become an urgent problem for those skilled in the art.
技术问题technical problem
本申请实施例提供了一种任务分配方法、装置、计算机可读存储介质及终端设备,能够进行合理、准确的任务分配,提高任务的分配效率和分配合理性。The embodiments of the present application provide a task allocation method, device, computer-readable storage medium, and terminal equipment, which can perform reasonable and accurate task allocation, and improve the efficiency and rationality of task allocation.
技术解决方案Technical solutions
本申请实施例的第一方面,提供了一种任务分配方法,包括:The first aspect of the embodiments of the present application provides a task allocation method, including:
获取待分配任务对应的各第一属性特征;Acquiring each first attribute characteristic corresponding to the task to be assigned;
将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节点、以任务等级为决策结果的模型;Each of the first attribute characteristics is input to a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model is based on the attribute A model with features as nodes and task levels as decision-making results;
根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;Determining the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。A corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be assigned is sent to a terminal corresponding to the target employee to prompt the target employee to process the task to be assigned.
本申请实施例的第二方面,提供了一种任务分配装置,包括:In a second aspect of the embodiments of the present application, a task allocation device is provided, including:
属性特征获取模块,用于获取待分配任务对应的各第一属性特征;The attribute feature obtaining module is used to obtain each first attribute feature corresponding to the task to be assigned;
任务等级确定模块,用于将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节点、以任务等级为决策结果的模型;The task level determination module is configured to input each of the first attribute characteristics into a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model Suppose the decision tree model is a model with attribute features as nodes and task levels as decision results;
候选员工组确定模块,用于根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;The candidate employee group determining module is used to determine the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
任务分配模块,用于基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。The task assignment module is used to select the corresponding target employee from the candidate employee group based on a preset selection method, and send the task to be assigned to the terminal corresponding to the target employee to prompt the target employee to Tasks to be assigned for processing.
本申请实施例的第三方面,提供了一种计算机可读存储介质,所述计算机可读存储介质存储有计算机可读指令,所述计算机可读指令被处理器执行时实现前述第一方面所述任务分配方法的步骤。The third aspect of the embodiments of the present application provides a computer-readable storage medium, the computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the foregoing first aspect is implemented. Describe the steps of the task allocation method.
本申请实施例的第四方面,提供了一种终端设备,包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机可读指令,所述处理器执行所述计算机可读指令时实现如下步骤:In a fourth aspect of the embodiments of the present application, a terminal device is provided, including a memory, a processor, and computer-readable instructions stored in the memory and running on the processor, and the processor executes the The following steps are implemented when computer readable instructions are:
获取待分配任务对应的各第一属性特征;Acquiring each first attribute characteristic corresponding to the task to be assigned;
将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节点、以任务等级为决策结果的模型;Each of the first attribute characteristics is input to a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model is based on the attribute A model with features as nodes and task levels as decision-making results;
根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;Determining the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。A corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be assigned is sent to a terminal corresponding to the target employee to prompt the target employee to process the task to be assigned.
有益效果Beneficial effect
本申请实施例中,在获取到待分配任务之后,可获取待分配任务对应的各第一属性特征,随后可将各第一属性特征输入至预设决策树模型,得到待分配任务对应的第一任务等级,进而可根据预设对应关系确定出第一任务等级对应的候选员工组,并基于预设选取方式从候选员工组中选取对应的目标员工来进行待分配任务的自动分配,以通过预设决策树模型对待分配任务的各第一属性特征进行全面分析来准确确定待分配任务的任务等级,从而可根据任务等级进行合理、准确的任务分配,实现任务分配的自动化和标准化,减少任务分配中的人力成本,提高任务分配效率和分配合理性。In the embodiment of the present application, after obtaining the task to be assigned, each first attribute feature corresponding to the task to be assigned can be obtained, and then each first attribute feature can be input to the preset decision tree model to obtain the first attribute feature corresponding to the task to be assigned A task level, the candidate employee group corresponding to the first task level can be determined according to the preset correspondence relationship, and the corresponding target employee can be selected from the candidate employee group based on the preset selection method to automatically assign the tasks to be assigned, so as to pass The preset decision tree model performs a comprehensive analysis of the first attribute characteristics of the tasks to be assigned to accurately determine the task level of the task to be assigned, so that a reasonable and accurate task assignment can be carried out according to the task level, so as to realize the automation and standardization of task assignment and reduce tasks The labor cost in the distribution improves the efficiency and rationality of task distribution.
附图说明Description of the drawings
为了更清楚地说明本申请实施例中的技术方案,下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本申请的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动性的前提下,还可以根据这些附图获得其他的附图。In order to more clearly describe the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only of the present application. For some embodiments, those of ordinary skill in the art can obtain other drawings based on these drawings without creative labor.
图1为本申请实施例中一种任务分配方法的一个实施例流程图;FIG. 1 is a flowchart of an embodiment of a task allocation method in an embodiment of this application;
图2为本申请实施例中一种任务分配方法在一个应用场景下构建预设决策树模型的流程示意图;FIG. 2 is a schematic flowchart of a task allocation method in an application scenario for constructing a preset decision tree model in an embodiment of the application;
图3为本申请实施例中一种任务分配方法在一个应用场景下进行任务分配的流程示意图;FIG. 3 is a schematic diagram of a process of task allocation in an application scenario of a task allocation method in an embodiment of the application;
图4为本申请实施例中一种任务分配方法在另一个应用场景下进行任务分配的流程示意图;FIG. 4 is a schematic flowchart of a task allocation method in an embodiment of the application for task allocation in another application scenario;
图5为本申请实施例中一种任务分配装置的一个实施例结构图;FIG. 5 is a structural diagram of an embodiment of a task distribution device in an embodiment of the application;
图6为本申请一实施例提供的一种终端设备的示意图。Fig. 6 is a schematic diagram of a terminal device provided by an embodiment of the application.
本发明的实施方式Embodiments of the present invention
本申请实施例提供了一种任务分配方法、装置、计算机可读存储介质及终端设备,用于进行合理、准确的任务分配,提高任务分配效率和分配合理性。The embodiments of the present application provide a task allocation method, device, computer-readable storage medium, and terminal equipment, which are used to perform reasonable and accurate task allocation and improve task allocation efficiency and rationality.
为使得本申请的发明目的、特征、优点能够更加的明显和易懂,下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进行清楚、完整地描述,显然,下面所描述的实施例仅仅是本申请一部分实施例,而非全部的实施例。基于本申请中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例,都属于本申请保护的范围。此外,术语“第一”、“第二”和“第三”等是用于区别不同对象,而非用于描述特定顺序。In order to make the purposes, features, and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the following The described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of this application. In addition, the terms "first", "second", and "third" are used to distinguish different objects, rather than describing a specific order.
如图1所示,本申请实施例提供了一种任务分配方法,所述任务分配方法包括:As shown in FIG. 1, an embodiment of the present application provides a task allocation method, and the task allocation method includes:
步骤S101、获取待分配任务对应的各第一属性特征;Step S101: Obtain each first attribute feature corresponding to the task to be assigned;
本申请实施例的执行主体为终端设备,所述终端设备包括但不限于:桌上型计算机、笔记本、掌上电脑及云端服务器等计算设备。在此,当用户需要进行任务分配时,用户可将待分配任务上传或者发送至所述终端设备,其中,所上传或者发送的待分配任务中可包括该待分配任务的介绍内容等。所述终端设备在接收到所述待分配任务时,则可从所对应的介绍内容中获取所述待分配任务对应的各第一属性特征,如可事先为各第一属性特征设置对应的关键词,所述终端设备则可通过对所述介绍内容进行关键词检索来获取各第一属性特征。The execution subject of the embodiments of the present application is a terminal device, and the terminal device includes, but is not limited to, computing devices such as desktop computers, notebooks, palmtop computers, and cloud servers. Here, when the user needs to perform task allocation, the user can upload or send the task to be allocated to the terminal device, where the uploaded or sent task to be allocated may include the introduction content of the task to be allocated, etc. When the terminal device receives the task to be assigned, it can obtain each first attribute feature corresponding to the task to be assigned from the corresponding introduction content, for example, a corresponding key can be set for each first attribute feature in advance Words, the terminal device can obtain each first attribute feature by performing a keyword search on the introduction content.
例如,在待分配任务为销售名单的应用场景中,可使用Excel文件等形式来存储销售名单,其中,所述销售名单可以为有购买相关的产品或者服务可能性的人员名单,并可将存储有所述销售名单的Excel文件上传或者发送至所述终端设备,所述终端设备则可从Excel文件中提取所述销售名单对应的种类、区域、来源、年龄、职业等第一属性特征。For example, in an application scenario where the task to be assigned is a sales list, the sales list can be stored in the form of an Excel file, where the sales list can be a list of people who are likely to purchase related products or services, and can be stored The Excel file containing the sales list is uploaded or sent to the terminal device, and the terminal device can extract the first attribute characteristics such as the category, region, source, age, and occupation corresponding to the sales list from the Excel file.
步骤S102、将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节 点、以任务等级为决策结果的模型;Step S102: Input each of the first attribute characteristics into a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model It is a model that takes attribute characteristics as nodes and task level as decision-making results;
可以理解的是,所述终端设备在获取到所述待分配任务对应的各第一属性特征后,可将各第一属性特征输入至预设决策树模型,所述预设决策树模型为以各属性特征为节点、以对应的任务等级为决策结果的模型,所述预设决策树模型则可将各第一属性特征与决策树中的各节点进行匹配,以此确定出所述待分配任务所对应的第一任务等级。It is understandable that, after acquiring each first attribute feature corresponding to the task to be assigned, the terminal device can input each first attribute feature into a preset decision tree model, and the preset decision tree model is Each attribute feature is a node, and the corresponding task level is a model of the decision result. The preset decision tree model can match each first attribute feature with each node in the decision tree to determine the to-be-assigned The first task level corresponding to the task.
在此,所述第一任务等级用于表示所述待分配任务的任务质量,其中,所述任务质量可基于所述待分配任务对应的预测分配结果来确定,预测分配结果是指所预测的待分配任务的分配成功率(或销售成功率)等,如可基于所述销售名单的预测销售结果来评价所述销售名单的任务质量,以构建所述销售名单所对应的第一任务等级。例如,可将预测销售结果(如预测销售成功率)高于90%的销售名单所对应的第一任务等级确定为优等级,表示该销售名单的质量很好;可将预测销售结果位于75%至90%之间的销售名单所对应的第一任务等级确定为良等级,表示该销售名单的质量较好;可将预测销售结果位于60%至75%之间的销售名单所对应的第一任务等级确定为中等级,表示该销售名单的质量一般;以及可将预测销售结果低于60%的销售名单所对应的第一任务等级确定为差等级,表示该销售名单的质量较差,等等。Here, the first task level is used to indicate the task quality of the task to be allocated, wherein the task quality can be determined based on the predicted allocation result corresponding to the task to be allocated, and the predicted allocation result refers to the predicted allocation result. The distribution success rate (or sales success rate) of the tasks to be allocated, for example, can evaluate the task quality of the sales list based on the predicted sales results of the sales list, so as to construct the first task level corresponding to the sales list. For example, the first task level corresponding to the sales list whose predicted sales result (such as the predicted sales success rate) is higher than 90% can be determined as the excellent level, indicating that the quality of the sales list is very good; the predicted sales result can be located at 75% The first task level corresponding to the sales list between 90% and 90% is determined as the good level, indicating that the quality of the sales list is good; the first task level corresponding to the sales list with the predicted sales result between 60% and 75% can be determined. The task level is determined to be medium, which means that the quality of the sales list is average; and the first task level corresponding to the sales list whose predicted sales result is less than 60% can be determined as the poor level, which means that the quality of the sales list is poor, etc. Wait.
进一步地,如图2所示,在一个具体应用场景中,所述预设决策树模型通过下述步骤构建:Further, as shown in Figure 2, in a specific application scenario, the preset decision tree model is constructed through the following steps:
步骤S201、获取预设数量的历史分配数据,其中,所述历史分配数据包括各历史任务对应的第二属性特征和第二分配结果;Step S201: Obtain a preset number of historical distribution data, where the historical distribution data includes second attribute characteristics and second distribution results corresponding to each historical task;
步骤S202、根据各所述第二分配结果确定各所述第二属性特征对应的属性权重,并根据各所述属性权重和各所述第二分配结果确定各所述历史任务对应的第二分配等级;Step S202: Determine the attribute weight corresponding to each of the second attribute characteristics according to each of the second assignment results, and determine the second assignment corresponding to each of the historical tasks according to each of the attribute weights and each of the second assignment results grade;
本场景中,在构建所述预设决策树模型时,可首先获取历史分配数据,所获取的各历史分配数据则可包括各历史任务所对应的第二属性特征和第二分配结果,其中,所述第二分配结果可包括分配成功和分配失败;其次,可对所有第二分配结果进行大数据分析,以确定出各所述第二属性特征所对应的历史任务的分配成功率,并可根据各所述第二属性特征的分配成功率来确定各所述第二属性特征对应的属性权重,如可对所有第二分配结果进行大数据分析,以确定出第二属性特征(如来源)的分配成功率,即可获取包含第二属性特征(来源)、且分配成功的历史任务的个数,并将该个数/历史任务的总个数,以此得到包含第二属性特征(来源)的分配成功率,该分配成功率越高,则第二属性特征(来源)对应的属性权重越大,反之,该分配成功率越低,则第二属性特征(来源)对应的属性权重越小。In this scenario, when constructing the preset decision tree model, the historical distribution data may be obtained first, and each obtained historical distribution data may include the second attribute feature and the second distribution result corresponding to each historical task. Among them, The second allocation result may include allocation success and allocation failure; secondly, big data analysis can be performed on all the second allocation results to determine the allocation success rate of the historical task corresponding to each of the second attribute characteristics, and Determine the attribute weight corresponding to each of the second attribute features according to the distribution success rate of each of the second attribute features. For example, big data analysis can be performed on all the second assignment results to determine the second attribute feature (such as the source) The allocation success rate of, you can get the number of historical tasks that contain the second attribute feature (source) and have been successfully allocated, and combine this number/the total number of historical tasks to obtain the second attribute feature (source) ) Distribution success rate, the higher the distribution success rate, the greater the attribute weight corresponding to the second attribute feature (source), on the contrary, the lower the distribution success rate, the higher the attribute weight corresponding to the second attribute feature (source) small.
进一步地,在得到各第二属性特征对应的属性权重后,则可根据第二属性特征对应的 属性权重,得到各历史任务对应的第二任务等级,例如,可根据:
Figure PCTCN2019116633-appb-000001
来确定包含多个属性特征的各历史任务的最终分配成功率,该最终分配成功率即表示该历史任务的任务质量,因此,可根据所对应的最终分配成功率来确定各历史任务的第二任务等级,以通过综合考虑多个属性特征和多个属性特征对应的属性权重来准确分析各历史任务的任务等级,确保任务等级确定的合理性和有效性,其中,SuccRate r为第r个历史任务对应的最终分配成功率,FeaValue rt为第r个历史任务的第t个第二属性特征所对应的分配成功率,Weight rt为第r个历史任务的第t个第二属性特征对应的属性权重,Quotiety r为第r个历史任务对应的加权系数。
Further, after the attribute weight corresponding to each second attribute feature is obtained, the second task level corresponding to each historical task can be obtained according to the attribute weight corresponding to the second attribute feature, for example, according to:
Figure PCTCN2019116633-appb-000001
To determine the final allocation success rate of each historical task containing multiple attribute characteristics, the final allocation success rate represents the task quality of the historical task, therefore, the second allocation success rate of each historical task can be determined according to the corresponding final allocation success rate. The task level is to accurately analyze the task level of each historical task by comprehensively considering multiple attribute features and attribute weights corresponding to multiple attribute features to ensure the rationality and effectiveness of the task level determination. Among them, SuccRate r is the rth history The final allocation success rate corresponding to the task, FeaValue rt is the allocation success rate corresponding to the t-th second attribute feature of the r-th historical task, and Weight rt is the attribute corresponding to the t-th second attribute feature of the r-th historical task Weight, Quotiety r is the weighting coefficient corresponding to the rth historical task.
步骤S203、基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,并根据各所述信息增益和各所述第二属性特征进行决策树的节点构建;Step S203: Calculate the information gain of each of the second attribute features based on each of the attribute weights and each of the second task levels, and construct the nodes of the decision tree according to each of the information gains and each of the second attribute features ;
步骤S204、根据所构建的节点和各所述第二任务等级构建所述预设决策树模型。Step S204: Construct the preset decision tree model according to the constructed node and each of the second task levels.
优选地,本场景中,所述基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,可以包括:Preferably, in this scenario, the calculating the information gain of each second attribute feature based on each of the attribute weights and each of the second task levels may include:
根据下述公式计算所述历史分配数据构成的数据集的属性熵Entropy(S):Calculate the attribute entropy Entropy(S) of the data set formed by the historical distribution data according to the following formula:
Figure PCTCN2019116633-appb-000002
Figure PCTCN2019116633-appb-000002
其中,S为历史分配数据构成的数据集,n为数据集所包含的第二任务等级的总个数,p i为数据集中第i个第二任务等级所占的比例; Among them, S is a data set composed of historical distribution data, n is the total number of second task levels included in the data set, and p i is the proportion of the i-th second task level in the data set;
根据所述属性熵和所述属性权重按照下述公式计算各所述第二属性特征的信息增益:Calculate the information gain of each second attribute feature according to the attribute entropy and the attribute weight according to the following formula:
Figure PCTCN2019116633-appb-000003
Figure PCTCN2019116633-appb-000003
其中,Gain(S,d)为第二属性特征d的信息增益,m为根据第二属性特征d对数据集进行划分得到的数据子集的个数,|S|为数据集中的数据数目,|S j|为第j个数据子集中的数据数目,Wegiht(d)为第二属性特征d对应的属性权重。 Among them, Gain(S,d) is the information gain of the second attribute feature d, m is the number of data subsets obtained by dividing the data set according to the second attribute feature d, |S| is the number of data in the data set, |S j | is the number of data in the jth data subset, and Wegiht(d) is the attribute weight corresponding to the second attribute feature d.
在此,可根据各第二属性特征的信息增益来构建决策树的每一级非叶子节点,其中,信息增益越大,该信息增益所对应的第二属性特征在决策树中所对应的节点级数则越高,如可首先根据信息增益对第二属性特征进行排序,然后可根据各历史分配数据确定判断条件,从而可根据排序后的第二属性特征和判断条件来构建决策树的各级非叶子节点,并可根据各历史分配任务对应的第二任务等级确定所构建的决策树中各叶子节点所对应的决策结果。即每一个非叶子节点为一个第二属性特征,节点之间的连线则可以为上一级节点至下一级节点所需满足的判断条件,而每一叶子节点则为一个决策结果,所述决策结果为满足由根节点至 该叶子节点中所有判断条件所对应的第二任务等级。在得到以第二属性特征为节点、以第二任务等级为决策结果的决策树后,则可将该决策树确定为所述预设决策树模型,通过属性熵和信息增益的计算来准确确定各属性特征在决策树中的节点位置、准确确定决策过程中的判断条件,确保预设决策树模型构建的准确性,从而提高待分配任务中任务等级确定的准确性。Here, the non-leaf node of each level of the decision tree can be constructed according to the information gain of each second attribute feature, where the greater the information gain, the node corresponding to the second attribute feature corresponding to the information gain in the decision tree The higher the number of levels, for example, the second attribute feature can be sorted according to the information gain first, and then the judgment condition can be determined according to each historical distribution data, so that each of the decision tree can be constructed according to the sorted second attribute feature and the judgment condition. Level is not a leaf node, and the decision result corresponding to each leaf node in the constructed decision tree can be determined according to the second task level corresponding to each historical assignment task. That is, each non-leaf node is a second attribute feature, the connection between nodes can be the judgment condition that the upper level node to the next level node needs to meet, and each leaf node is a decision result, so The decision result is the second task level corresponding to all the judgment conditions from the root node to the leaf node. After the decision tree with the second attribute feature as the node and the second task level as the decision result is obtained, the decision tree can be determined as the preset decision tree model, which can be accurately determined through the calculation of attribute entropy and information gain The node position of each attribute feature in the decision tree and the judgment conditions in the decision-making process are accurately determined to ensure the accuracy of the construction of the preset decision tree model, thereby improving the accuracy of the task level determination in the task to be assigned.
本场景中,通过对大量历史分配数据进行大数据分析来确定各属性特征的属性权重,并通过计算得到各历史分配数据的信息增益,从而根据信息增益和属性权重来准确确定各属性特征在决策树中的节点位置,可确保预设决策树模型构建的准确性,从而提高后续待分配任务中任务等级确定的准确性。In this scenario, the attribute weight of each attribute feature is determined by performing big data analysis on a large amount of historical distribution data, and the information gain of each historical distribution data is obtained by calculation, so as to accurately determine the decision-making of each attribute feature according to the information gain and attribute weight The position of the node in the tree can ensure the accuracy of the construction of the preset decision tree model, thereby improving the accuracy of task level determination in the subsequent tasks to be assigned.
可选地,本场景中,在将所述待分配任务发送至所述目标员工对应的终端之后,可以包括:Optionally, in this scenario, after sending the task to be assigned to the terminal corresponding to the target employee, it may include:
获取所述待分配任务对应的第一分配结果,并基于所述待分配任务对应的第一分配结果和所述第一属性特征更新所述历史分配数据,以根据更新后的历史分配数据更新所述预设决策树模型。Obtain the first allocation result corresponding to the task to be allocated, and update the historical allocation data based on the first allocation result corresponding to the task to be allocated and the first attribute feature, so as to update the allocating data according to the updated historical allocation data. The pre-set decision tree model is described.
在此,在完成所述待分配任务的分配,并获取到对应的第一分配结果后,可将所述待分配任务对应的分配数据(包括第一分配结果和各第一属性特性)作为数据样本来更新决策树中所选取的历史分配数据,以根据更新后的历史分配数据对决策树进行更新,即通过实时更新、增加决策树构建中的数据样本来得到任务等级确定更合理、更准确的预设决策树模型。Here, after the assignment of the task to be assigned is completed and the corresponding first assignment result is obtained, the assignment data (including the first assignment result and each first attribute characteristic) corresponding to the task to be assigned can be used as the data Samples are used to update the selected historical distribution data in the decision tree to update the decision tree according to the updated historical distribution data, that is, through real-time updating and increasing the data samples in the decision tree construction, the task level determination is more reasonable and more accurate The preset decision tree model.
步骤S103、根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;Step S103: Determine the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
本申请实施例,还可预先设置任务等级与员工组之间的预设对应关系,其中,员工组的组数与任务等级的等级数相同,而员工组可根据各员工的工作能力等进行划分,如可根据各员工的工作能力等对各员工进行评分,并根据评分所在的分值区间对各员工进行分组划分,得到多个员工组,如可将评分位于第一分值区间(如90分以上)的员工划分至第一员工组、将评分位于第二分值区间(如80至90分)的员工划分至第二员工组、将评分位于第三分值区间(如70至80分)的员工划分至第三员工组,以及将评分位于第四分值区间(如低于70分)的员工划分至第四员工组。在此,预先设置的任务等级与员工组之间的预设对应关系则可以为:第一员工组与优等级对应、第二员工组与良等级对应、第三员工组与中等级对应、第四员工组与差等级对应。In the embodiment of this application, a preset correspondence relationship between task levels and employee groups can also be set in advance, wherein the number of groups of employee groups is the same as the number of levels of task levels, and the employee groups can be divided according to the work ability of each employee, etc. For example, each employee can be scored according to their work ability, etc., and each employee can be divided into groups according to the score interval in which the score is located, and multiple employee groups can be obtained. For example, the score can be placed in the first score interval (such as 90 The employees with scores above) are divided into the first employee group, the employees whose scores are in the second score range (such as 80 to 90 points) are divided into the second employee group, and the scores are in the third score range (such as 70 to 80 points). ) Are divided into the third employee group, and employees whose scores are in the fourth score range (for example, less than 70 points) are divided into the fourth employee group. Here, the preset corresponding relationship between the preset task level and the employee group can be: the first employee group corresponds to the excellent level, the second employee group corresponds to the good level, the third employee group corresponds to the middle level, and the second employee group corresponds to the good level. The four employee groups correspond to the difference level.
因此,在利用所述预设决策树模型确定了所述待分配任务对应的第一任务等级后,所述第一任务等级为所述任务等级中的某一个具体等级,则可根据所述预设对应关系确定出所述第一任务等级对应的候选员工组,其中,所述候选员工组为所述员工组中的某一个具体员 工组。如当确定所述待分配任务对应的第一任务等级为优等级时,则可确定出所对应的候选员工组为第一员工组;而当确定所述待分配任务对应的第一任务等级为中等级时,则可确定出所对应的候选员工组为第三员工组,等等。Therefore, after the first task level corresponding to the task to be assigned is determined by using the preset decision tree model, and the first task level is a specific level of the task levels, it can be determined according to the preset decision tree model. It is assumed that the corresponding relationship determines the candidate employee group corresponding to the first task level, where the candidate employee group is a specific employee group in the employee group. For example, when it is determined that the first task level corresponding to the task to be assigned is an excellent level, it can be determined that the corresponding candidate employee group is the first employee group; and when it is determined that the first task level corresponding to the task to be assigned is medium When leveling, it can be determined that the corresponding candidate employee group is the third employee group, and so on.
步骤S104、基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。Step S104: Select a corresponding target employee from the candidate employee group based on a preset selection method, and send the task to be assigned to the terminal corresponding to the target employee to prompt the target employee to respond to the task to be assigned To process.
可以理解的是,在确定出所述待分配任务对应的候选员工组后,则可从所述候选员工组中确定目标员工来进行任务的自动分配。本申请实施例中,可预先设置各员工组所对应的预设选取方式,以通过该员工组所对应的预设选取方式从该员工组中进行目标员工的选取。例如,可设置第一员工组对应的预设选取方式为随机的选取方式、可设置第二员工组对应的预设选取方式为基于按处理能力的选取方式(即处理能力越强的员工越容易被选取)、可设置第三员工组对应的预设选取方式为基于积压任务量的选取方式(即积压任务量越少的员工越容易被选取),等等。因此,在确定出所述待分配任务对应的候选员工组之后,则可获取该候选员工组所对应的预设选取方式,从而可基于该预设选取方式从该候选员工组中选取对应的目标员工,并可将所述待分配任务自动发送至所选取的目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。It is understandable that after the candidate employee group corresponding to the task to be assigned is determined, the target employee can be determined from the candidate employee group for automatic task assignment. In the embodiment of the present application, the preset selection method corresponding to each employee group can be set in advance, so that the target employee can be selected from the employee group through the preset selection method corresponding to the employee group. For example, the default selection method corresponding to the first group of employees can be set to random selection, and the default selection method corresponding to the second group of employees can be set to the selection method based on processing capabilities (that is, the more capable employees are, the easier it is. Selected), the default selection method corresponding to the third employee group can be set to the selection method based on the backlog amount of tasks (that is, the lesser the backlog amount of tasks, the easier it is to be selected), and so on. Therefore, after the candidate employee group corresponding to the task to be assigned is determined, the preset selection method corresponding to the candidate employee group can be obtained, so that the corresponding target can be selected from the candidate employee group based on the preset selection method Employees, and can automatically send the task to be assigned to the terminal corresponding to the selected target employee to prompt the target employee to process the task to be assigned.
优选地,在一个具体应用场景中,可为所有员工组设置相同的预设选取方式,如可将所有员工组的预设选取方式均设置为基于处理能力和积压任务量的选取方式。因此,如图3所示,所述基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,可以包括:Preferably, in a specific application scenario, the same preset selection method can be set for all employee groups. For example, the preset selection methods of all employee groups can be set to a selection method based on processing capabilities and backlog tasks. Therefore, as shown in FIG. 3, selecting a corresponding target employee from the candidate employee group based on a preset selection method, and sending the task to be assigned to a terminal corresponding to the target employee, may include:
步骤S301、获取所述候选员工组的任务状态,并根据所述任务状态确定所述候选员工组中的空闲员工;Step S301: Obtain the task status of the candidate employee group, and determine the idle employees in the candidate employee group according to the task status;
步骤S302、根据各所述空闲员工的分配记录确定各所述空闲员工的任务处理能力,并根据所述任务处理能力对各所述空闲员工进行降序排列,得到排列数组;Step S302: Determine the task processing ability of each idle employee according to the allocation record of each idle employee, and sort the idle employees in descending order according to the task processing ability to obtain a permutation array;
步骤S303、将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端。Step S303: The idle employee ranked first in the arrangement array is selected as the target employee corresponding to the task to be assigned, and the task to be assigned is sent to the terminal corresponding to the target employee.
对于上述步骤S301至步骤S303,可以理解的是,在确定所述待分配任务对应的候选员工组后,可获取所述候选员工组的任务状态,如获取所述候选员工组中各员工的积压任务量等,从而可根据任务状态来确定所述候选员工组中各员工目前的任务状态,以此确定出任务状态处于空闲状态的员工,即从所述候选员工组中找出目前无任务处理的空闲员工,当所找出的空闲员工为一个时,则可直接将所述待分配任务发送至该空闲员工对应的终端。For the above steps S301 to S303, it can be understood that after the candidate employee group corresponding to the task to be assigned is determined, the task status of the candidate employee group can be obtained, such as obtaining the backlog of each employee in the candidate employee group Task quantity, etc., so that the current task status of each employee in the candidate employee group can be determined according to the task status, so as to determine the employees whose task status is idle, that is, to find out from the candidate employee group that there is currently no task processing If there is only one idle employee found, the task to be assigned can be directly sent to the terminal corresponding to the idle employee.
而当所找出的空闲员工有多个时,则可获取各空闲员工的分配记录,即获取各空闲员 工已经处理完的历史任务的任务处理记录,以根据各历史任务的任务记录来确定各空闲员工的任务处理能力,其中,任务处理能力可利用各空闲员工的任务处理成功率来衡量,任务处理成功率越高,则所对应的任务处理能力越强。在确定出各空闲员工的任务处理能力后,则可根据任务处理能力对各空闲员工进行降序排列,得到降序排列的排列数组,在该排列数组中,任务处理能力越强的空闲员工排序越靠前,并将该排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,即将各空闲员工中任务处理能力最强的空闲员工确定为所述待分配任务对应的目标员工,并可将所述待分配任务发送至该目标员工对应的终端,以提高任务分配的准确性和效率。When there are multiple idle employees found, the allocation record of each idle employee can be obtained, that is, the task processing record of the historical task that each idle employee has processed, so as to determine each idle employee according to the task record of each historical task. The task processing ability of employees. Among them, the task processing ability can be measured by the task processing success rate of each idle employee. The higher the task processing success rate, the stronger the corresponding task processing ability. After the task processing ability of each idle employee is determined, the idle employees can be sorted in descending order according to the task processing ability, and a descending array is obtained. In this array, the idle employees with the stronger task processing ability are sorted more reliably Before, the first idle employee in the array is selected as the target employee corresponding to the task to be assigned, that is, the idle employee with the strongest task processing ability among the idle employees is determined as the target employee corresponding to the task to be assigned , And the task to be allocated can be sent to the terminal corresponding to the target employee to improve the accuracy and efficiency of task allocation.
优选地,如图4所示,所述将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,并将所述待分任务发送至所述目标员工对应的终端,可以包括:Preferably, as shown in FIG. 4, the first idle employee in the arrangement array is selected as the target employee corresponding to the task to be assigned, and the task to be assigned is sent to the target employee corresponding to the target employee. The terminal can include:
步骤S401、将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求,并接收所述终端返回的回复信息;Step S401: Select the first idle employee in the arrangement array as the target employee corresponding to the task to be assigned, send a task assignment request to the terminal corresponding to the target employee, and receive reply information returned by the terminal;
步骤S402、判断所述回复信息是否为确认接收所述待分配任务;Step S402: Determine whether the reply message is to confirm the reception of the task to be assigned;
步骤S403、当所述回复信息为确认接收所述待分配任务时,则将所述待分配任务发送至所述目标员工对应的终端;Step S403: When the reply message is to confirm receipt of the task to be assigned, the task to be assigned is sent to the terminal corresponding to the target employee;
步骤S404、当所述回复信息为拒绝接收所述待分配任务时,则将排序第一的空闲员工移动至所述排列数组的末位,以更新所述排列数组,并返回执行将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求的步骤以及后续步骤。Step S404: When the reply message is to refuse to receive the task to be assigned, move the idle employee ranked first to the end of the permutation array to update the permutation array, and return to execute the permutation The first-ranked idle employee in the array is selected as the target employee corresponding to the task to be assigned, and the steps and subsequent steps of sending a task assignment request to the terminal corresponding to the target employee.
对于上述步骤S401至步骤S404,本申请实施例中,在确定出所述待分配任务对应的目标员工后,可首先向所述目标员工对应的终端发送任务分配请求,以通过所述目标员工对所述任务分配请求的回复信息来确定所述目标员工是否能接收所述待分配任务,从而确保任务分配的正确性和有效性。当所述目标员工返回的回复信息表明所述目标员工确认接收所述待分配任务时,则将所述待分配任务发送至所述目标员工对应的终端;而当所述目标员工返回的回复信息表明所述目标员工无法接收所述待分配任务时,则可从所述排列数组中选取下一位空闲员工来执行任务的分配操作,即可将排序第一的空闲员工移动至所述排列数组的末位来更新所述排列数组,并将更新后的排列数组中排序第一的空闲员工重新选取为所述待分配任务对应的目标员工,然后再进行任务分配请求的发送,直到存在空闲员工接收所述待分配任务为止,以通过任务分配前任务分配请求的发送来及时、有效地进行任务的分配,避免分配后的退回重分配等,从而提高任务的分配效率。For the above steps S401 to S404, in the embodiment of the present application, after the target employee corresponding to the task to be assigned is determined, the task assignment request may be first sent to the terminal corresponding to the target employee, so as to pass the target employee to the target employee. The reply information of the task assignment request is used to determine whether the target employee can receive the task to be assigned, so as to ensure the correctness and effectiveness of the task assignment. When the reply information returned by the target employee indicates that the target employee confirms to receive the task to be assigned, the task to be assigned is sent to the terminal corresponding to the target employee; and when the target employee returns the reply information When it indicates that the target employee cannot receive the task to be assigned, the next idle employee can be selected from the permutation array to perform the task assignment operation, and the idle employee with the first ranking can be moved to the permutation array To update the permutation array, and reselect the idle employee ranked first in the updated permutation array as the target employee corresponding to the task to be assigned, and then send the task assignment request until there is an idle employee Until the task to be allocated is received, the task allocation can be performed in a timely and effective manner by sending the task allocation request before the task allocation, so as to avoid the return and redistribution after the allocation, so as to improve the task allocation efficiency.
本申请实施例中,在获取到待分配任务之后,可获取待分配任务对应的各第一属性特 征,随后可将各第一属性特征输入至预设决策树模型,得到待分配任务对应的第一任务等级,进而可根据预设对应关系确定出第一任务等级对应的候选员工组,并基于预设选取方式从候选员工组中选取对应的目标员工来进行待分配任务的自动分配,以通过预设决策树模型对待分配任务的各属性特征进行全面分析来准确确定待分配任务的任务等级,从而可根据任务等级进行合理、准确的任务分配,实现任务分配的自动化和标准化,减少任务分配中的人力成本,提高任务分配效率和分配合理性。In the embodiment of the present application, after obtaining the task to be assigned, each first attribute feature corresponding to the task to be assigned can be obtained, and then each first attribute feature can be input into the preset decision tree model to obtain the first attribute feature corresponding to the task to be assigned A task level, the candidate employee group corresponding to the first task level can be determined according to the preset corresponding relationship, and the corresponding target employee can be selected from the candidate employee group based on the preset selection method to automatically assign the tasks to be assigned, so as to pass The preset decision tree model performs a comprehensive analysis of the attributes and characteristics of the tasks to be assigned to accurately determine the task level of the task to be assigned, so that reasonable and accurate task assignment can be carried out according to the task level, so as to realize the automation and standardization of task assignment, and reduce the task distribution The labor cost is improved, and the task allocation efficiency and the rationality of the allocation are improved.
应理解,上述实施例中各步骤的序号的大小并不意味着执行顺序的先后,各过程的执行顺序应以其功能和内在逻辑确定,而不应对本申请实施例的实施过程构成任何限定。It should be understood that the size of the sequence number of each step in the foregoing embodiment does not mean the order of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.
上面主要描述了一种任务分配方法,下面将对一种任务分配装置进行详细描述。A task distribution method is mainly described above, and a task distribution device will be described in detail below.
如图5所示,本申请实施例提供了一种任务分配装置,所述任务分配装置包括:As shown in FIG. 5, an embodiment of the present application provides a task allocation device, and the task allocation device includes:
属性特征获取模块501,用于获取待分配任务对应的各第一属性特征;The attribute feature acquiring module 501 is configured to acquire each first attribute feature corresponding to the task to be assigned;
任务等级确定模块502,用于将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节点、以任务等级为决策结果的模型;The task level determination module 502 is configured to input each of the first attribute characteristics into a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, where the The preset decision tree model is a model that takes attribute features as nodes and task levels as decision results;
候选员工组确定模块503,用于根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;The candidate employee group determining module 503 is configured to determine the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
任务分配模块504,用于基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。The task allocation module 504 is configured to select a corresponding target employee from the candidate employee group based on a preset selection method, and send the task to be assigned to the terminal corresponding to the target employee to prompt the target employee to The tasks to be assigned are processed.
进一步地,所述任务分配装置,还可以包括:Further, the task distribution device may further include:
历史分配数据获取模块,用于获取预设数量的历史分配数据,其中,所述历史分配数据包括各历史任务对应的第二属性特征和第二分配结果;The historical allocation data acquisition module is configured to acquire a preset number of historical allocation data, where the historical allocation data includes the second attribute characteristics and second allocation results corresponding to each historical task;
属性权重确定模块,用于根据各所述第二分配结果确定各所述第二属性特征对应的属性权重,并根据各所述属性权重和各所述第二分配结果确定各所述历史任务对应的第二任务等级;The attribute weight determination module is configured to determine the attribute weight corresponding to each of the second attribute characteristics according to each of the second assignment results, and determine the corresponding historical task according to each of the attribute weights and each of the second assignment results The second task level;
信息增益计算模块,用于基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,并根据各所述信息增益和各所述第二属性特征进行决策树的节点构建;The information gain calculation module is configured to calculate the information gain of each of the second attribute features based on each of the attribute weights and each of the second task levels, and make a decision based on each of the information gains and each of the second attribute features Node construction of the tree;
决策树模型构建模块,用于根据所构建的节点和各所述第二任务等级构建所述预设决策树模型。The decision tree model construction module is used to construct the preset decision tree model according to the constructed node and each of the second task levels.
优选地,所述信息增益计算模块,可以包括:Preferably, the information gain calculation module may include:
属性熵计算单元,用于根据下述公式计算所述历史分配数据构成的数据集的属性熵 Entropy(S):The attribute entropy calculation unit is configured to calculate the attribute entropy Entropy(S) of the data set formed by the historical distribution data according to the following formula:
Figure PCTCN2019116633-appb-000004
Figure PCTCN2019116633-appb-000004
其中,S为历史分配数据构成的数据集,n为数据集所包含的第二任务等级的总个数,p i为数据集中第i个第二任务等级所占的比例; Among them, S is a data set composed of historical distribution data, n is the total number of second task levels included in the data set, and p i is the proportion of the i-th second task level in the data set;
信息增益计算单元,用于根据所述属性熵和所述属性权重按照下述公式计算各所述第二属性特征的信息增益:The information gain calculation unit is configured to calculate the information gain of each second attribute feature according to the attribute entropy and the attribute weight according to the following formula:
Figure PCTCN2019116633-appb-000005
Figure PCTCN2019116633-appb-000005
其中,Gain(S,d)为第二属性特征d的信息增益,m为根据第二属性特征d对数据集进行划分得到的数据子集的个数,|S|为数据集中的数据数目,|S j|为第j个数据子集中的数据数目,Wegiht(d)为第二属性特征d对应的属性权重。 Among them, Gain(S,d) is the information gain of the second attribute feature d, m is the number of data subsets obtained by dividing the data set according to the second attribute feature d, |S| is the number of data in the data set, |S j | is the number of data in the jth data subset, and Wegiht(d) is the attribute weight corresponding to the second attribute feature d.
可选地,所述任务分配装置,还可以包括:Optionally, the task distribution device may further include:
模型更新模块,用于获取所述待分配任务对应的第一分配结果,并基于所述待分配任务对应的第一分配结果和所述第一属性特征更新所述历史分配数据,以根据更新后的历史分配数据更新所述预设决策树模型。The model update module is used to obtain the first allocation result corresponding to the task to be allocated, and to update the historical allocation data based on the first allocation result corresponding to the task to be allocated and the first attribute feature, so as to update the historical allocation data according to the updated task. Update the preset decision tree model with the historical distribution data of.
进一步地,所述任务分配模块504,可以包括:Further, the task allocation module 504 may include:
空闲员工确定单元,用于获取所述候选员工组的任务状态,并根据所述任务状态确定所述候选员工组中的空闲员工;An idle employee determining unit, configured to obtain the task status of the candidate employee group, and determine the idle employees in the candidate employee group according to the task status;
排列数组获取单元,用于根据各所述空闲员工的分配记录确定各所述空闲员工的任务处理能力,并根据所述任务处理能力对各所述空闲员工进行降序排列,得到排列数组;The permutation array acquisition unit is used to determine the task processing capability of each idle employee according to the allocation record of each idle employee, and arrange the idle employees in descending order according to the task processing capability to obtain the permutation array;
任务分配单元,用于将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端。The task allocation unit is configured to select the idle employee ranked first in the arrangement array as the target employee corresponding to the task to be allocated, and send the task to be allocated to the terminal corresponding to the target employee.
优选地,所述任务分配单元,可以包括:Preferably, the task allocation unit may include:
分配请求发送分单元,用于将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求,并接收所述终端返回的回复信息;The allocation request sending sub-unit is used to select the first idle employee in the arrangement array as the target employee corresponding to the task to be allocated, send a task allocation request to the terminal corresponding to the target employee, and receive the terminal Reply information returned;
任务分配分单元,用于当所述回复信息为确认接收所述待分配任务时,则将所述待分配任务发送至所述目标员工对应的终端;The task allocation sub-unit is configured to send the task to be allocated to the terminal corresponding to the target employee when the reply message is to confirm receipt of the task to be allocated;
排列数组更新单元,用于当所述回复信息为拒绝接收所述待分配任务时,则将排序第一的空闲员工移动至所述排列数组的末位,以更新所述排列数组,并返回执行将所述排列数 组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求的步骤以及后续步骤。The permutation array update unit is used for when the reply message is to refuse to receive the task to be assigned, move the first-ranked idle employee to the last position of the permutation array to update the permutation array and return to execution The first-ranked idle employee in the arrangement array is selected as the target employee corresponding to the task to be assigned, and the step of sending a task assignment request to the terminal corresponding to the target employee and subsequent steps.
图6是本申请一实施例提供的终端设备的示意图。如图6所示,该实施例的终端设备6包括:处理器60、存储器61以及存储在所述存储器61中并可在所述处理器60上运行的计算机可读指令62,例如任务分配程序。所述处理器60执行所述计算机可读指令62时实现上述各个任务分配方法实施例中的步骤,例如图1所示的步骤S101至步骤S104。或者,所述处理器60执行所述计算机可读指令62时实现上述各装置实施例中各模块/单元的功能,例如图5所示的模块501至模块504的功能。Fig. 6 is a schematic diagram of a terminal device provided by an embodiment of the present application. As shown in FIG. 6, the terminal device 6 of this embodiment includes: a processor 60, a memory 61, and computer-readable instructions 62 stored in the memory 61 and running on the processor 60, such as a task allocation program . When the processor 60 executes the computer-readable instructions 62, the steps in the foregoing task allocation method embodiments are implemented, for example, steps S101 to S104 shown in FIG. 1. Alternatively, when the processor 60 executes the computer-readable instructions 62, the functions of the modules/units in the foregoing device embodiments, such as the functions of the modules 501 to 504 shown in FIG. 5, are implemented.
示例性的,所述计算机可读指令62可以被分割成一个或多个模块/单元,所述一个或者多个模块/单元被存储在所述存储器61中,并由所述处理器60执行,以完成本申请。所述一个或多个模块/单元可以是能够完成特定功能的一系列计算机可读指令段,该指令段用于描述所述计算机可读指令62在所述终端设备6中的执行过程。Exemplarily, the computer-readable instructions 62 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 61 and executed by the processor 60, To complete this application. The one or more modules/units may be a series of computer-readable instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer-readable instructions 62 in the terminal device 6.
所述终端设备6可以是桌上型计算机、笔记本、掌上电脑及云端服务器等计算设备。所述终端设备可包括,但不仅限于,处理器60、存储器61。本领域技术人员可以理解,图6仅仅是终端设备6的示例,并不构成对终端设备6的限定,可以包括比图示更多或更少的部件,或者组合某些部件,或者不同的部件,例如所述终端设备还可以包括输入输出设备、网络接入设备、总线等。The terminal device 6 may be a computing device such as a desktop computer, a notebook, a palmtop computer, and a cloud server. The terminal device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art can understand that FIG. 6 is only an example of the terminal device 6 and does not constitute a limitation on the terminal device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device may also include input and output devices, network access devices, buses, and the like.
所述处理器60可以是中央处理单元(Central Processing Unit,CPU),还可以是其他通用处理器、数字信号处理器(Digital Signal Processor,DSP)、专用集成电路(Application Specific Integrated Circuit,ASIC)、现成可编程门阵列(Field-Programmable Gate Array,FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。The processor 60 may be a central processing unit (Central Processing Unit, CPU), other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (ASIC), Ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
所述存储器61可以是所述终端设备6的内部存储单元,例如终端设备6的硬盘或内存。所述存储器61也可以是所述终端设备6的外部存储设备,例如所述终端设备6上配备的插接式硬盘,智能存储卡(Smart Media Card,SMC),安全数字(Secure Digital,SD)卡,闪存卡(Flash Card)等。进一步地,所述存储器61还可以既包括所述终端设备6的内部存储单元也包括外部存储设备。所述存储器61用于存储所述计算机可读指令以及所述终端设备所需的其他程序和数据。所述存储器61还可以用于暂时地存储已经输出或者将要输出的数据。The memory 61 may be an internal storage unit of the terminal device 6, such as a hard disk or a memory of the terminal device 6. The memory 61 may also be an external storage device of the terminal device 6, such as a plug-in hard disk equipped on the terminal device 6, a smart memory card (Smart Media Card, SMC), and a Secure Digital (SD) Card, Flash Card, etc. Further, the memory 61 may also include both an internal storage unit of the terminal device 6 and an external storage device. The memory 61 is used to store the computer-readable instructions and other programs and data required by the terminal device. The memory 61 can also be used to temporarily store data that has been output or will be output.
另外,在本申请各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现,也可以采用软件功能单元的形式实现。In addition, the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时,可以存储在一个计算机可读取存储介质中。If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程,是可以通过计算机可读指令来指令相关的硬件来完成,所述的计算机可读指令可存储于一计算机非易失性可读取存储介质中,该计算机可读指令在执行时,可包括如上述各方法的实施例的流程。其中,本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用,均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限,RAM以多种形式可得,诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。A person of ordinary skill in the art can understand that all or part of the processes in the method of the above-mentioned embodiments can be implemented by instructing relevant hardware through computer-readable instructions. The computer-readable instructions can be stored in a non-volatile computer. In a readable storage medium, when the computer-readable instructions are executed, they may include the processes of the above-mentioned method embodiments. Wherein, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and/or volatile memory. Non-volatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not a limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Channel (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
以上所述,以上实施例仅用以说明本申请的技术方案,而非对其限制;尽管参照前述实施例对本申请进行了详细的说明,本领域的普通技术人员应当理解:其依然可以对前述各实施例所记载的技术方案进行修改,或者对其中部分技术特征进行等同替换;而这些修改或者替换,并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。As mentioned above, the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions recorded in the embodiments are modified, or some of the technical features are equivalently replaced; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims (20)

  1. 一种任务分配方法,其特征在于,包括:A task allocation method is characterized in that it includes:
    获取待分配任务对应的各第一属性特征;Acquiring each first attribute characteristic corresponding to the task to be assigned;
    将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节点、以任务等级为决策结果的模型;Each of the first attribute characteristics is input to a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model is based on the attribute A model with features as nodes and task levels as decision-making results;
    根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;Determining the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
    基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。A corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be assigned is sent to a terminal corresponding to the target employee to prompt the target employee to process the task to be assigned.
  2. 根据权利要求1所述的任务分配方法,其特征在于,所述预设决策树模型通过下述步骤构建:The task allocation method according to claim 1, wherein the preset decision tree model is constructed through the following steps:
    获取预设数量的历史分配数据,其中,所述历史分配数据包括各历史任务对应的第二属性特征和第二分配结果;Acquiring a preset number of historical distribution data, where the historical distribution data includes the second attribute feature and the second distribution result corresponding to each historical task;
    根据各所述第二分配结果确定各所述第二属性特征对应的属性权重,并根据各所述属性权重和各所述第二分配结果确定各所述历史任务对应的第二任务等级;Determine the attribute weight corresponding to each of the second attribute features according to each of the second assignment results, and determine the second task level corresponding to each of the historical tasks according to each of the attribute weights and each of the second assignment results;
    基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,并根据各所述信息增益和各所述第二属性特征进行决策树的节点构建;Calculating the information gain of each of the second attribute characteristics based on each of the attribute weights and each of the second task levels, and constructing nodes of the decision tree according to each of the information gains and each of the second attribute characteristics;
    根据所构建的节点和各所述第二任务等级构建所述预设决策树模型。The preset decision tree model is constructed according to the constructed node and each of the second task levels.
  3. 根据权利要求2所述的任务分配方法,其特征在于,所述基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,包括:The task allocation method according to claim 2, wherein the calculating the information gain of each second attribute feature based on each of the attribute weights and each of the second task levels comprises:
    根据下述公式计算所述历史分配数据构成的数据集的属性熵Entropy(S):Calculate the attribute entropy Entropy(S) of the data set formed by the historical distribution data according to the following formula:
    Figure PCTCN2019116633-appb-100001
    Figure PCTCN2019116633-appb-100001
    其中,S为历史分配数据构成的数据集,n为数据集所包含的第二任务等级的总个数,p i为数据集中第i个第二任务等级所占的比例; Among them, S is a data set composed of historical distribution data, n is the total number of second task levels included in the data set, and p i is the proportion of the i-th second task level in the data set;
    根据所述属性熵和所述属性权重按照下述公式计算各所述第二属性特征的信息增益:Calculate the information gain of each second attribute feature according to the attribute entropy and the attribute weight according to the following formula:
    Figure PCTCN2019116633-appb-100002
    Figure PCTCN2019116633-appb-100002
    其中,Gain(S,d)为第二属性特征d的信息增益,m为根据第二属性特征d对数据集进行划分得到的数据子集的个数,|S|为数据集中的数据数目,|S j|为第j个数据子集中的数据 数目,Wegiht(d)为第二属性特征d对应的属性权重。 Among them, Gain(S,d) is the information gain of the second attribute feature d, m is the number of data subsets obtained by dividing the data set according to the second attribute feature d, |S| is the number of data in the data set, |S j | is the number of data in the jth data subset, and Wegiht(d) is the attribute weight corresponding to the second attribute feature d.
  4. 根据权利要求2所述的任务分配方法,其特征在于,在将所述待分配任务发送至所述目标员工对应的终端之后,包括:The task allocation method according to claim 2, wherein after the task to be allocated is sent to the terminal corresponding to the target employee, the method comprises:
    获取所述待分配任务对应的第一分配结果,并基于所述待分配任务对应的第一分配结果和所述第一属性特征更新所述历史分配数据,以根据更新后的历史分配数据更新所述预设决策树模型。Obtain the first allocation result corresponding to the task to be allocated, and update the historical allocation data based on the first allocation result corresponding to the task to be allocated and the first attribute feature, so as to update the allocating data according to the updated historical allocation data. The pre-set decision tree model is described.
  5. 根据权利要求1至4中任一项所述的任务分配方法,其特征在于,所述基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,包括:The task allocation method according to any one of claims 1 to 4, wherein the corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be allocated is sent to The terminal corresponding to the target employee includes:
    获取所述候选员工组的任务状态,并根据所述任务状态确定所述候选员工组中的空闲员工;Acquiring the task status of the candidate employee group, and determining idle employees in the candidate employee group according to the task status;
    根据各所述空闲员工的分配记录确定各所述空闲员工的任务处理能力,并根据所述任务处理能力对各所述空闲员工进行降序排列,得到排列数组;Determine the task processing capability of each idle employee according to the allocation record of each idle employee, and sort the idle employees in descending order according to the task processing capability to obtain a permutation array;
    将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端。The idle employee ranked first in the permutation array is selected as the target employee corresponding to the task to be assigned, and the task to be assigned is sent to the terminal corresponding to the target employee.
  6. 根据权利要求5所述的任务分配方法,其特征在于,所述将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,包括:The task allocation method according to claim 5, wherein the first idle employee in the arrangement array is selected as the target employee corresponding to the task to be allocated, and the task to be allocated is sent to The terminal corresponding to the target employee includes:
    将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求,并接收所述终端返回的回复信息;Selecting the first idle employee in the arrangement array as the target employee corresponding to the task to be assigned, sending a task assignment request to the terminal corresponding to the target employee, and receiving reply information returned by the terminal;
    当所述回复信息为确认接收所述待分配任务时,则将所述待分配任务发送至所述目标员工对应的终端;When the reply message is confirmation of receiving the task to be assigned, sending the task to be assigned to the terminal corresponding to the target employee;
    当所述回复信息为拒绝接收所述待分配任务时,则将排序第一的空闲员工移动至所述排列数组的末位,以更新所述排列数组,并返回执行将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求的步骤以及后续步骤。When the reply message is to refuse to receive the task to be assigned, move the idle employee ranked first to the end of the permutation array to update the permutation array, and return to execute the sorting in the permutation array The first idle employee selects the target employee corresponding to the task to be assigned, and sends the task assignment request step and subsequent steps to the terminal corresponding to the target employee.
  7. 一种任务分配装置,其特征在于,包括:A task distribution device is characterized in that it comprises:
    属性特征获取模块,用于获取待分配任务对应的各第一属性特征;The attribute feature obtaining module is used to obtain each first attribute feature corresponding to the task to be assigned;
    任务等级确定模块,用于将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节点、以任务等级为决策结果的模型;The task level determination module is configured to input each of the first attribute characteristics into a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model Suppose the decision tree model is a model with attribute features as nodes and task levels as decision results;
    候选员工组确定模块,用于根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;The candidate employee group determining module is used to determine the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
    任务分配模块,用于基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。The task assignment module is used to select the corresponding target employee from the candidate employee group based on a preset selection method, and send the task to be assigned to the terminal corresponding to the target employee to prompt the target employee to Tasks to be assigned for processing.
  8. 根据权利要求7所述的任务分配装置,其特征在于,所述任务分配装置,还包括:8. The task distribution device according to claim 7, wherein the task distribution device further comprises:
    历史分配数据获取模块,用于获取预设数量的历史分配数据,其中,所述历史分配数据包括各历史任务对应的第二属性特征和第二分配结果;The historical allocation data acquisition module is configured to acquire a preset number of historical allocation data, where the historical allocation data includes the second attribute characteristics and second allocation results corresponding to each historical task;
    属性权重确定模块,用于根据各所述第二分配结果确定各所述第二属性特征对应的属性权重,并根据各所述属性权重和各所述第二分配结果确定各所述历史任务对应的第二任务等级;The attribute weight determination module is configured to determine the attribute weight corresponding to each of the second attribute characteristics according to each of the second assignment results, and determine the corresponding historical task according to each of the attribute weights and each of the second assignment results The second task level;
    信息增益计算模块,用于基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,并根据各所述信息增益和各所述第二属性特征进行决策树的节点构建;The information gain calculation module is configured to calculate the information gain of each of the second attribute features based on each of the attribute weights and each of the second task levels, and make a decision based on each of the information gains and each of the second attribute features Node construction of the tree;
    决策树模型构建模块,用于根据所构建的节点和各所述第二任务等级构建所述预设决策树模型。The decision tree model construction module is used to construct the preset decision tree model according to the constructed node and each of the second task levels.
  9. 根据权利要求8所述的任务分配装置,其特征在于,所述信息增益计算模块,包括:8. The task distribution device according to claim 8, wherein the information gain calculation module comprises:
    属性熵计算单元,用于根据下述公式计算所述历史分配数据构成的数据集的属性熵Entropy(S):The attribute entropy calculation unit is configured to calculate the attribute entropy Entropy(S) of the data set formed by the historical distribution data according to the following formula:
    Figure PCTCN2019116633-appb-100003
    Figure PCTCN2019116633-appb-100003
    其中,S为历史分配数据构成的数据集,n为数据集所包含的第二任务等级的总个数,p i为数据集中第i个第二任务等级所占的比例; Among them, S is a data set composed of historical distribution data, n is the total number of second task levels included in the data set, and p i is the proportion of the i-th second task level in the data set;
    信息增益计算单元,用于根据所述属性熵和所述属性权重按照下述公式计算各所述第二属性特征的信息增益:The information gain calculation unit is configured to calculate the information gain of each second attribute feature according to the attribute entropy and the attribute weight according to the following formula:
    Figure PCTCN2019116633-appb-100004
    Figure PCTCN2019116633-appb-100004
    其中,Gain(S,d)为第二属性特征d的信息增益,m为根据第二属性特征d对数据集进行划分得到的数据子集的个数,|S|为数据集中的数据数目,|Sj|为第j个数据子集中的数据数目,Wegiht(d)为第二属性特征d对应的属性权重。Among them, Gain(S,d) is the information gain of the second attribute feature d, m is the number of data subsets obtained by dividing the data set according to the second attribute feature d, |S| is the number of data in the data set, |Sj| is the number of data in the jth data subset, and Wegiht(d) is the attribute weight corresponding to the second attribute feature d.
  10. 根据权利要求8所述的任务分配装置,其特征在于,所述任务分配装置,包括:8. The task distribution device according to claim 8, wherein the task distribution device comprises:
    模型更新模块,用于获取所述待分配任务对应的第一分配结果,并基于所述待分配任 务对应的第一分配结果和所述第一属性特征更新所述历史分配数据,以根据更新后的历史分配数据更新所述预设决策树模型。The model update module is used to obtain the first allocation result corresponding to the task to be allocated, and to update the historical allocation data based on the first allocation result corresponding to the task to be allocated and the first attribute feature, so as to update the historical allocation data according to the updated task Update the preset decision tree model with the historical distribution data of.
  11. 根据权利要求7至10中任一项所述的任务分配装置,其特征在于,所述任务分配模块,包括:The task distribution device according to any one of claims 7 to 10, wherein the task distribution module comprises:
    空闲员工确定单元,用于获取所述候选员工组的任务状态,并根据所述任务状态确定所述候选员工组中的空闲员工;An idle employee determining unit, configured to obtain the task status of the candidate employee group, and determine the idle employees in the candidate employee group according to the task status;
    排列数组获取单元,用于根据各所述空闲员工的分配记录确定各所述空闲员工的任务处理能力,并根据所述任务处理能力对各所述空闲员工进行降序排列,得到排列数组;The permutation array acquisition unit is used to determine the task processing capability of each idle employee according to the allocation record of each idle employee, and arrange the idle employees in descending order according to the task processing capability to obtain the permutation array;
    任务分配单元,用于将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端。The task allocation unit is configured to select the idle employee ranked first in the arrangement array as the target employee corresponding to the task to be allocated, and send the task to be allocated to the terminal corresponding to the target employee.
  12. 根据权利要求11所述的任务分配装置,其特征在于,所述任务分配单元,包括:The task allocation device according to claim 11, wherein the task allocation unit comprises:
    分配请求发送分单元,用于将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求,并接收所述终端返回的回复信息;The allocation request sending sub-unit is used to select the first idle employee in the arrangement array as the target employee corresponding to the task to be allocated, send a task allocation request to the terminal corresponding to the target employee, and receive the terminal Reply information returned;
    任务分配分单元,用于当所述回复信息为确认接收所述待分配任务时,则将所述待分配任务发送至所述目标员工对应的终端;The task allocation sub-unit is configured to send the task to be allocated to the terminal corresponding to the target employee when the reply message is to confirm receipt of the task to be allocated;
    排列数组更新单元,用于当所述回复信息为拒绝接收所述待分配任务时,则将排序第一的空闲员工移动至所述排列数组的末位,以更新所述排列数组,并返回执行将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求的步骤以及后续步骤。The permutation array update unit is used to move the idle employee ranked first to the end of the permutation array to update the permutation array and return to execution when the reply message is that the task to be assigned is rejected The first-ranked idle employee in the arrangement array is selected as the target employee corresponding to the task to be assigned, and the step of sending a task assignment request to the terminal corresponding to the target employee and subsequent steps.
  13. 一种计算机可读存储介质,所述计算机可读存储介质存储有计算机可读指令,其特征在于,所述计算机可读指令被处理器执行时实现如下步骤:A computer-readable storage medium, the computer-readable storage medium storing computer-readable instructions, wherein the computer-readable instructions are executed by a processor to implement the following steps:
    获取待分配任务对应的各第一属性特征;Acquiring each first attribute characteristic corresponding to the task to be assigned;
    将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节点、以任务等级为决策结果的模型;Each of the first attribute characteristics is input to a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model is based on the attribute A model with features as nodes and task levels as decision-making results;
    根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;Determining the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
    基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。A corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be assigned is sent to a terminal corresponding to the target employee to prompt the target employee to process the task to be assigned.
  14. 根据权利要求13所述的计算机可读存储介质,其特征在于,所述预设决策树模型通过下述步骤构建:The computer-readable storage medium according to claim 13, wherein the preset decision tree model is constructed through the following steps:
    获取预设数量的历史分配数据,其中,所述历史分配数据包括各历史任务对应的第二属性特征和第二分配结果;Acquiring a preset number of historical distribution data, where the historical distribution data includes the second attribute feature and the second distribution result corresponding to each historical task;
    根据各所述第二分配结果确定各所述第二属性特征对应的属性权重,并根据各所述属性权重和各所述第二分配结果确定各所述历史任务对应的第二任务等级;Determine the attribute weight corresponding to each of the second attribute features according to each of the second assignment results, and determine the second task level corresponding to each of the historical tasks according to each of the attribute weights and each of the second assignment results;
    基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,并根据各所述信息增益和各所述第二属性特征进行决策树的节点构建;Calculating the information gain of each of the second attribute characteristics based on each of the attribute weights and each of the second task levels, and constructing nodes of the decision tree according to each of the information gains and each of the second attribute characteristics;
    根据所构建的节点和各所述第二任务等级构建所述预设决策树模型。The preset decision tree model is constructed according to the constructed node and each of the second task levels.
  15. 一种终端设备,包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机可读指令,其特征在于,所述处理器执行所述计算机可读指令时实现如下步骤:A terminal device, comprising a memory, a processor, and computer-readable instructions stored in the memory and running on the processor, wherein the processor executes the computer-readable instructions as follows step:
    获取待分配任务对应的各第一属性特征;Acquiring each first attribute characteristic corresponding to the task to be assigned;
    将各所述第一属性特征输入至预设决策树模型,得到所述预设决策树模型输出的所述待分配任务对应的第一任务等级,其中,所述预设决策树模型为以属性特征为节点、以任务等级为决策结果的模型;Each of the first attribute characteristics is input to a preset decision tree model to obtain the first task level corresponding to the task to be assigned output by the preset decision tree model, wherein the preset decision tree model is based on the attribute A model with features as nodes and task levels as decision-making results;
    根据任务等级与员工组之间的预设对应关系确定所述第一任务等级对应的候选员工组;Determining the candidate employee group corresponding to the first task level according to the preset correspondence between the task level and the employee group;
    基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,以提示所述目标员工对所述待分配任务进行处理。A corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be assigned is sent to a terminal corresponding to the target employee to prompt the target employee to process the task to be assigned.
  16. 根据权利要求15所述的终端设备,其特征在于,所述预设决策树模型通过下述步骤构建:The terminal device according to claim 15, wherein the preset decision tree model is constructed through the following steps:
    获取预设数量的历史分配数据,其中,所述历史分配数据包括各历史任务对应的第二属性特征和第二分配结果;Acquiring a preset number of historical distribution data, where the historical distribution data includes the second attribute feature and the second distribution result corresponding to each historical task;
    根据各所述第二分配结果确定各所述第二属性特征对应的属性权重,并根据各所述属性权重和各所述第二分配结果确定各所述历史任务对应的第二任务等级;Determine the attribute weight corresponding to each of the second attribute features according to each of the second assignment results, and determine the second task level corresponding to each of the historical tasks according to each of the attribute weights and each of the second assignment results;
    基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,并根据各所述信息增益和各所述第二属性特征进行决策树的节点构建;Calculating the information gain of each of the second attribute characteristics based on each of the attribute weights and each of the second task levels, and constructing nodes of the decision tree according to each of the information gains and each of the second attribute characteristics;
    根据所构建的节点和各所述第二任务等级构建所述预设决策树模型。The preset decision tree model is constructed according to the constructed node and each of the second task levels.
  17. 根据权利要求16所述的终端设备,其特征在于,所述基于各所述属性权重和各所述第二任务等级计算各所述第二属性特征的信息增益,包括:The terminal device according to claim 16, wherein the calculating the information gain of each of the second attribute features based on each of the attribute weights and each of the second task levels comprises:
    根据下述公式计算所述历史分配数据构成的数据集的属性熵Entropy(S):Calculate the attribute entropy Entropy(S) of the data set formed by the historical distribution data according to the following formula:
    Figure PCTCN2019116633-appb-100005
    Figure PCTCN2019116633-appb-100005
    其中,S为历史分配数据构成的数据集,n为数据集所包含的第二任务等级的总个数, p i为数据集中第i个第二任务等级所占的比例; Among them, S is a data set composed of historical distribution data, n is the total number of second task levels contained in the data set, and p i is the proportion of the i-th second task level in the data set;
    根据所述属性熵和所述属性权重按照下述公式计算各所述第二属性特征的信息增益:Calculate the information gain of each second attribute feature according to the attribute entropy and the attribute weight according to the following formula:
    Figure PCTCN2019116633-appb-100006
    Figure PCTCN2019116633-appb-100006
    其中,Gain(S,d)为第二属性特征d的信息增益,m为根据第二属性特征d对数据集进行划分得到的数据子集的个数,|S|为数据集中的数据数目,|S j|为第j个数据子集中的数据数目,Wegiht(d)为第二属性特征d对应的属性权重。 Among them, Gain(S,d) is the information gain of the second attribute feature d, m is the number of data subsets obtained by dividing the data set according to the second attribute feature d, |S| is the number of data in the data set, |S j | is the number of data in the jth data subset, and Wegiht(d) is the attribute weight corresponding to the second attribute feature d.
  18. 根据权利要求16所述的终端设备,其特征在于,在将所述待分配任务发送至所述目标员工对应的终端之后,包括:获取所述待分配任务对应的第一分配结果,并基于所述待分配任务对应的第一分配结果和所述第一属性特征更新所述历史分配数据,以根据更新后的历史分配数据更新所述预设决策树模型。The terminal device according to claim 16, characterized in that, after sending the task to be assigned to the terminal corresponding to the target employee, it comprises: obtaining a first assignment result corresponding to the task to be assigned, and based on the The first assignment result corresponding to the task to be assigned and the first attribute feature update the historical assignment data, so as to update the preset decision tree model according to the updated historical assignment data.
  19. 根据权利要求15至18中任一项所述的终端设备,其特征在于,所述基于预设选取方式从所述候选员工组中选取对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,包括:The terminal device according to any one of claims 15 to 18, wherein the corresponding target employee is selected from the candidate employee group based on a preset selection method, and the task to be assigned is sent to all Describe the terminal corresponding to the target employee, including:
    获取所述候选员工组的任务状态,并根据所述任务状态确定所述候选员工组中的空闲员工;Acquiring the task status of the candidate employee group, and determining idle employees in the candidate employee group according to the task status;
    根据各所述空闲员工的分配记录确定各所述空闲员工的任务处理能力,并根据所述任务处理能力对各所述空闲员工进行降序排列,得到排列数组;Determine the task processing capability of each idle employee according to the allocation record of each idle employee, and sort the idle employees in descending order according to the task processing capability to obtain a permutation array;
    将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端。The idle employee ranked first in the permutation array is selected as the target employee corresponding to the task to be assigned, and the task to be assigned is sent to the terminal corresponding to the target employee.
  20. 根据权利要求19所述的终端设备,其特征在于,所述将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,并将所述待分配任务发送至所述目标员工对应的终端,包括:The terminal device according to claim 19, wherein the first idle employee in the arrangement array is selected as the target employee corresponding to the task to be allocated, and the task to be allocated is sent to all Describe the terminal corresponding to the target employee, including:
    将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求,并接收所述终端返回的回复信息;Selecting the first idle employee in the arrangement array as the target employee corresponding to the task to be assigned, sending a task assignment request to the terminal corresponding to the target employee, and receiving reply information returned by the terminal;
    当所述回复信息为确认接收所述待分配任务时,则将所述待分配任务发送至所述目标员工对应的终端;When the reply message is confirmation of receiving the task to be assigned, sending the task to be assigned to the terminal corresponding to the target employee;
    当所述回复信息为拒绝接收所述待分配任务时,则将排序第一的空闲员工移动至所述排列数组的末位,以更新所述排列数组,并返回执行将所述排列数组中排序第一的空闲员工选取为所述待分配任务对应的目标员工,向所述目标员工对应的终端发送任务分配请求的步骤以及后续步骤。When the reply message is to refuse to receive the task to be assigned, move the idle employee ranked first to the end of the permutation array to update the permutation array, and return to execute the sorting in the permutation array The first idle employee selects the target employee corresponding to the task to be assigned, and sends the task assignment request step and subsequent steps to the terminal corresponding to the target employee.
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