CN112508331A - Method, equipment and storage medium for allocating worker resources - Google Patents
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Abstract
The embodiment of the application provides a method and equipment for allocating worker resources and a storage medium. In some embodiments of the present application, the worker resource allocation device receives historical recruitment data and attribute data of a plurality of candidate brokers transmitted by at least one business terminal; determining conversion degrees and affinity degrees of the candidate brokers according to historical recruitment data and attribute data of the candidate brokers, wherein the conversion degrees reflect the capacity of the candidate brokers to recruit workers, and the affinity degrees reflect the affinity degrees of the candidate brokers with the resource data; selecting a target broker from the plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers; and sending the resource data to be distributed to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be distributed, thereby improving the distribution efficiency of tasks and improving the user experience.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method, a device, and a storage medium for allocating worker resources.
Background
Currently, home companies acquire information of a large number of workers through various channels. The information of a large number of workers needs to be relatively evenly distributed to each broker team, and manual distribution is carried out by a broker supervisor according to the personal conditions of the broker. The current task allocation mode has the problems of low allocation efficiency and unreasonable allocation.
Disclosure of Invention
Aspects of the present application provide a method, device and storage medium for allocating worker resources, which improve task allocation efficiency and improve user experience.
The embodiment of the application provides a method for allocating worker resources, which comprises the following steps:
receiving historical recruitment data and attribute data of a plurality of candidate brokers sent by at least one business terminal;
determining a degree of conversion and a degree of affinity of the plurality of candidate brokers according to historical recruitment data and attribute data of the plurality of candidate brokers, wherein the degree of conversion reflects the ability of the candidate brokers to recruit workers and the degree of affinity reflects the degree of affinity of the candidate brokers with the resource data;
selecting a target broker from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers;
and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting the laborers according to the resource data to be allocated.
An embodiment of the present application further provides a worker resource allocation device, including: a memory, a processor, and a communication component;
the memory for storing a computer program;
the communication component is used for establishing communication connection with other equipment;
the processor to execute the computer program to:
receiving, by a communication component, historical recruitment data and attribute data of a plurality of candidate brokers transmitted by at least one business terminal;
determining a degree of conversion and a degree of affinity of the plurality of candidate brokers according to historical recruitment data and attribute data of the plurality of candidate brokers, wherein the degree of conversion reflects the ability of the candidate brokers to recruit workers and the degree of affinity reflects the degree of affinity of the candidate brokers with the resource data;
selecting a target broker from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers;
and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting the laborers according to the resource data to be allocated.
Embodiments of the present application also provide a computer-readable storage medium storing a computer program that, when executed by one or more processors, causes the one or more processors to perform actions comprising:
receiving historical recruitment data and attribute data of a plurality of candidate brokers sent by at least one business terminal;
determining a degree of conversion and a degree of affinity of the plurality of candidate brokers according to historical recruitment data and attribute data of the plurality of candidate brokers, wherein the degree of conversion reflects the ability of the candidate brokers to recruit workers and the degree of affinity reflects the degree of affinity of the candidate brokers with the resource data;
selecting a target broker from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers;
and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting the laborers according to the resource data to be allocated.
In some embodiments of the present application, the worker resource allocation device receives historical recruitment data and attribute data of a plurality of candidate brokers transmitted by at least one business terminal; determining conversion degrees and affinity degrees of the candidate brokers according to historical recruitment data and attribute data of the candidate brokers, wherein the conversion degrees reflect the capacity of the candidate brokers to recruit workers, and the affinity degrees reflect the affinity degrees of the candidate brokers with the resource data; selecting a target broker from the plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers; and sending the resource data to be distributed to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be distributed, thereby improving the distribution efficiency of tasks and improving the user experience.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a block diagram of a worker resource allocation system provided in an exemplary embodiment of the present application;
FIG. 2 is a flowchart illustrating a method for allocating labor resources according to an embodiment of the present disclosure;
FIG. 3 is a schematic flow chart diagram of another worker resource allocation method provided in an exemplary embodiment of the present application;
FIG. 4 is a schematic flow chart diagram of another worker resource allocation method provided in an exemplary embodiment of the present application;
FIG. 5 is a schematic flow chart diagram of another worker resource allocation method provided in an exemplary embodiment of the present application;
FIG. 6 is a schematic diagram of a structure of a worker resource allocation device according to an exemplary embodiment of the present application;
FIG. 7 is a schematic structural diagram of a worker resource allocation device according to an exemplary embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Currently, home companies acquire information of a large number of workers through various channels. The information of a large number of workers needs to be relatively evenly distributed to each broker team, and manual distribution is carried out by a broker supervisor according to the personal conditions of the broker. The current task allocation mode has the problems of low allocation efficiency and unreasonable allocation.
In view of the above technical problem, in some embodiments of the present application, a worker resource allocation device receives historical recruitment data and attribute data of a plurality of candidate brokers transmitted by at least one business terminal; determining conversion degrees and affinity degrees of the candidate brokers according to historical recruitment data and attribute data of the candidate brokers, wherein the conversion degrees reflect the capacity of the candidate brokers to recruit workers, and the affinity degrees reflect the affinity degrees of the candidate brokers with the resource data; selecting a target broker from the plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers; and sending the resource data to be distributed to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be distributed, thereby improving the distribution efficiency of tasks and improving the user experience.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
FIG. 1 is a block diagram of a worker resource allocation system 10 according to an exemplary embodiment of the present application. As shown in FIG. 1, the worker resource allocation system 10 includes: at least one business terminal 10a, a worker resource allocation device 10b and a broker terminal 10 c.
In this embodiment, the at least one business terminal 10a and broker terminal 10c may be wirelessly or wired with the worker resource allocation device 10 b. Alternatively, at least one of the business terminal 10a and the broker terminal 10c may establish a communication connection with the worker resource allocation device 10b by using a communication method such as WIFI, bluetooth, infrared, and the like, and at least one of the business terminal 10a and the broker terminal 10c may establish a communication connection with the worker resource allocation device 10b by using a mobile network. The network format of the mobile network may be any one of 2G (gsm), 2.5G (gprs), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G + (LTE +), WiMax, and the like.
In the present embodiment, the worker resource allocation apparatus 10b receives the current task volume, the historical recruitment data, the attributes, and/or the status data of the plurality of candidate brokers transmitted by the at least one business terminal 10 a; determining the resource demand degree of the candidate brokers according to the current task amount, the historical recruitment data, the attribute and/or the state data of the candidate brokers, and selecting a target broker from the candidate brokers according to the resource demand degree of the candidate brokers; the resource data to be allocated is sent to the terminal device used by the target broker (i.e., the broker terminal 10 c), so that the target broker performs an operation of recruiting workers according to the resource data to be allocated.
It should be noted that the resource requirement in the foregoing embodiments includes, but is not limited to, the following: degree of conversion, affinity, idleness and load. The resource demand degree is not limited to the above forms, and can be adjusted according to actual conditions. The embodiment of the application can use one or more of conversion degree, affinity degree, idleness degree and load degree as a basis for selecting the target broker from a plurality of candidate brokers. The following description is provided for the conversion, affinity, idleness, and load, and for selecting a target broker from a plurality of candidate brokers based on one or more of the conversion, affinity, idleness, and load.
The following describes the manner of obtaining the conversion degree, affinity, vacancy degree and load degree in the examples of the present application.
Firstly, the acquisition mode of the conversion degree. Determining conversion rates of the candidate brokers according to historical recruitment data of the candidate brokers; based on the conversion rates of the plurality of candidate brokers, conversion rate scores for the plurality of candidate brokers are calculated, the conversion rate scores for the candidate brokers reflecting the conversion rates of the candidate brokers.
The historical recruitment data comprise total task amount and conversion success task amount distributed in unit time, and the conversion rates of the candidate brokers are determined according to the historical recruitment data of the candidate brokers. For example, if a broker successfully recruits 30 workers out of 100 recruiter assignments, the conversion rate for the broker is 30/100-0.3.
And secondly, obtaining the affinity. Determining working mode values of the candidate brokers according to the attribute data of the candidate brokers; calculating affinity scores for the plurality of candidate brokers based on the work pattern values for the plurality of candidate brokers, the affinity scores for the candidate brokers reflecting the affinity of the candidate brokers.
Thirdly, determining the task allocation interval scores of the candidate brokers according to the current task amount, the state and/or attribute data and the historical recruitment data of the candidate brokers in the idle degree acquisition mode; calculating idleness scores of the plurality of candidate brokers according to the assigned task interval scores of the plurality of candidate brokers, wherein the idleness scores reflect idleness of the candidate brokers.
The status of the candidate broker includes broker online and broker leave, and the attributes of the broker include, but are not limited to, the following: the city, the operator station, the task level, the source of the task channel and the personal ability. The historical recruitment data includes, but is not limited to, the following data: distribution of time intervals historically assigned to individuals, distribution of time intervals historically assigned to other individuals within the team, and the amount of tasks predicted based on historical data.
And fourthly, obtaining the load degree. Determining load rates of the candidate brokers according to current task volumes, state and/or attribute data and historical recruitment data of the candidate brokers; and calculating the load degree scores of the candidate brokers according to the load rates of the candidate brokers, wherein the load degree scores reflect the load degrees of the candidate brokers.
Determining the load rates of the candidate brokers according to the current task volumes, the states and/or the attribute data and the historical recruitment data of the candidate brokers, wherein one achievable mode is to calculate the load upper limits of the candidate brokers according to the current task volumes, the states and/or the attribute data and the historical recruitment data of the candidate brokers; and calculating the load rates of the candidate brokers according to the load upper limits and the current task amount of the candidate brokers. Optionally, the attributes of the candidate broker include, but are not limited to, the following: the city and the operation station; the historical recruitment data includes, but is not limited to, the following data: personal historical load, clue category.
In the above embodiment, the conversion rate score is calculated as f (x1) ═ k1 × 1^2+ n 1;
the calculation formula of the affinity score is that f (x2) ═ k2 × 2^2+ n 2;
the idleness score is calculated by the formula f (x3) ═ k3 × 3+ n 3;
the calculation formula of the load score is that f (x4) ═ k4/x4+ n 4;
wherein f (x1) is a conversion rate score, f (x2) is an affinity score, f (x3) is an idleness score, f (x4) is a load score, the value ranges of k1, k2, k3 and k4 are (0, 1), n1, n2, n3 and n4 are positive integers, x1 is a conversion rate, x2 is a working mode value, x3 is an allocation task interval score, and x4 is a load rate.
In one embodiment, a target broker is selected from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers, one achievable way is to calculate a first resource allocation value for the plurality of candidate brokers based on the degrees of conversion scores of the plurality of candidate brokers and the affinity scores of the plurality of candidate brokers; a target broker is selected from a plurality of candidate brokers based on a first resource allocation value of the plurality of candidate brokers. The first resource allocation value is calculated as Y ═ f (x1) × w1+ f (x2) × w2, where Y is the second resource allocation value, w1 is the conversion weight, and w2 is the affinity weight.
In another embodiment, the target broker is selected from the plurality of candidate brokers based on the idleness and load of the plurality of candidate brokers. One way in which this may be achieved is by calculating a second resource allocation value for the plurality of candidate brokers based on the idleness scores of the plurality of candidate brokers and the load scores of the plurality of candidate brokers; a target broker is selected from the plurality of candidate brokers based on the second resource allocation values for the plurality of candidate brokers. The first resource allocation value is calculated as Y ═ f (x3) × w3+ f (x4) × w4, where Y is the second resource allocation value, w3 is the idleness weight, and w4 is the loading weight.
In another embodiment, the target broker is selected from the plurality of candidate brokers based on a degree of conversion, an affinity, an idleness, and a load of the plurality of candidate brokers. Calculating a third resource allocation value for the plurality of candidate brokers based on the conversion score, the affinity score, the idleness score, and the load score for the plurality of candidate brokers; selecting a target broker from the plurality of candidate brokers based on the third resource allocation values for the plurality of candidate brokers. The first resource allocation value is calculated as Y ═ f (x1) × w1+ f (x2) × w2+ f (x3) × w3+ f (x4) × w4, where Y is the second resource allocation value, w1 is the transition weight, w2 is the affinity weight, w3 is the vacancy weight, and w4 is the load weight.
In the above system embodiment of the present application, the worker resource allocation device receives historical recruitment data, current task volume and status and/or attribute data of a plurality of candidate brokers sent by at least one business terminal; determining resource demand degrees of the candidate brokers according to historical recruitment data, current task amount and state and/or attribute data of the candidate brokers; selecting a target broker from the candidate brokers according to the resource demand degrees of the candidate brokers; and sending the resource data to be distributed to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be distributed, thereby improving the distribution efficiency of tasks and improving the user experience.
In addition to the worker resource allocation system 10 provided above, some embodiments of the present application also provide a worker resource allocation method, which can be implemented by relying on the worker resource allocation system 10, but is not limited to the worker resource allocation system 10 provided in the above embodiments.
Fig. 2 is a flowchart illustrating a method for allocating worker resources according to an embodiment of the present disclosure. As shown in fig. 2, the method includes:
s201: receiving historical recruitment data, current task amount and state and/or attribute data of a plurality of candidate brokers, which are sent by at least one business terminal;
s202: determining resource demand degrees of the candidate brokers according to historical recruitment data, current task amount and state and/or attribute data of the candidate brokers;
s203: selecting a target broker from the candidate brokers according to the resource demand degrees of the candidate brokers;
s204: and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be allocated.
In the embodiment, the worker resource allocation device receives current task volume, historical recruitment data, attributes and/or status data of a plurality of candidate brokers, which are sent by at least one business terminal; determining the resource demand degree of the candidate brokers according to the current task amount, the historical recruitment data, the attribute and/or the state data of the candidate brokers, and selecting a target broker from the candidate brokers according to the resource demand degree of the candidate brokers; and sending the resource data to be allocated to a terminal device (namely, a broker terminal) used by the target broker, so that the target broker executes the operation of recruiting workers according to the resource data to be allocated.
It should be noted that the resource requirement in the foregoing embodiments includes, but is not limited to, the following: degree of conversion, affinity, idleness and load. The resource demand degree is not limited to the above forms, and can be adjusted according to actual conditions. The embodiment of the application can use one or more of conversion degree, affinity degree, idleness degree and load degree as a basis for selecting the target broker from a plurality of candidate brokers. The following description is provided for the conversion, affinity, idleness, and load, and for selecting a target broker from a plurality of candidate brokers based on one or more of the conversion, affinity, idleness, and load.
The following describes the manner of obtaining the conversion degree, affinity, vacancy degree and load degree in the examples of the present application.
Firstly, the acquisition mode of the conversion degree. Determining conversion rates of the candidate brokers according to historical recruitment data of the candidate brokers; based on the conversion rates of the plurality of candidate brokers, conversion rate scores for the plurality of candidate brokers are calculated, the conversion rate scores for the candidate brokers reflecting the conversion rates of the candidate brokers.
The historical recruitment data comprise total task amount and conversion success task amount distributed in unit time, and the conversion rates of the candidate brokers are determined according to the historical recruitment data of the candidate brokers. For example, if a broker successfully recruits 30 workers out of 100 recruiter assignments, the conversion rate for the broker is 30/100-0.3.
And secondly, obtaining the affinity. Determining working mode values of the candidate brokers according to the attribute data of the candidate brokers; calculating affinity scores for the plurality of candidate brokers based on the work pattern values for the plurality of candidate brokers, the affinity scores for the candidate brokers reflecting the affinity of the candidate brokers.
Thirdly, determining the task allocation interval scores of the candidate brokers according to the current task amount, the state and/or attribute data and the historical recruitment data of the candidate brokers in the idle degree acquisition mode; calculating idleness scores of the plurality of candidate brokers according to the assigned task interval scores of the plurality of candidate brokers, wherein the idleness scores reflect idleness of the candidate brokers.
The status of the candidate broker includes broker online and broker leave, and the attributes of the broker include, but are not limited to, the following: the city, the operator station, the task level, the source of the task channel and the personal ability. The historical recruitment data includes, but is not limited to, the following data: distribution of time intervals historically assigned to individuals, distribution of time intervals historically assigned to other individuals within the team, and the amount of tasks predicted based on historical data.
And fourthly, obtaining the load degree. Determining load rates of the candidate brokers according to current task volumes, state and/or attribute data and historical recruitment data of the candidate brokers; and calculating the load degree scores of the candidate brokers according to the load rates of the candidate brokers, wherein the load degree scores reflect the load degrees of the candidate brokers.
Determining the load rates of the candidate brokers according to the current task volumes, the states and/or the attribute data and the historical recruitment data of the candidate brokers, wherein one achievable mode is to calculate the load upper limits of the candidate brokers according to the current task volumes, the states and/or the attribute data and the historical recruitment data of the candidate brokers; and calculating the load rates of the candidate brokers according to the load upper limits and the current task amount of the candidate brokers. Optionally, the attributes of the candidate broker include, but are not limited to, the following: the city and the operation station; the historical recruitment data includes, but is not limited to, the following data: personal historical load, clue category.
In the above embodiment, the conversion rate score is calculated as f (x1) ═ k1 × 1^2+ n 1;
the calculation formula of the affinity score is that f (x2) ═ k2 × 2^2+ n 2;
the idleness score is calculated by the formula f (x3) ═ k3 × 3+ n 3;
the calculation formula of the load score is that f (x4) ═ k4/x4+ n 4;
wherein f (x1) is a conversion rate score, f (x2) is an affinity score, f (x3) is an idleness score, f (x4) is a load score, the value ranges of k1, k2, k3 and k4 are (0, 1), n1, n2, n3 and n4 are positive integers, x1 is a conversion rate, x2 is a working mode value, x3 is an allocation task interval score, and x4 is a load rate.
In one embodiment, a target broker is selected from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers, one achievable way is to calculate a first resource allocation value for the plurality of candidate brokers based on the degrees of conversion scores of the plurality of candidate brokers and the affinity scores of the plurality of candidate brokers; a target broker is selected from a plurality of candidate brokers based on a first resource allocation value of the plurality of candidate brokers. The first resource allocation value is calculated as Y ═ f (x1) × w1+ f (x2) × w2, where Y is the second resource allocation value, w1 is the conversion weight, and w2 is the affinity weight.
In another embodiment, the target broker is selected from the plurality of candidate brokers based on the idleness and load of the plurality of candidate brokers. One way in which this may be achieved is by calculating a second resource allocation value for the plurality of candidate brokers based on the idleness scores of the plurality of candidate brokers and the load scores of the plurality of candidate brokers; a target broker is selected from the plurality of candidate brokers based on the second resource allocation values for the plurality of candidate brokers. The first resource allocation value is calculated as Y ═ f (x3) × w3+ f (x4) × w4, where Y is the second resource allocation value, w3 is the idleness weight, and w4 is the loading weight.
In another embodiment, the target broker is selected from the plurality of candidate brokers based on a degree of conversion, an affinity, an idleness, and a load of the plurality of candidate brokers. Calculating a third resource allocation value for the plurality of candidate brokers based on the conversion score, the affinity score, the idleness score, and the load score for the plurality of candidate brokers; selecting a target broker from the plurality of candidate brokers based on the third resource allocation values for the plurality of candidate brokers. The first resource allocation value is calculated as Y ═ f (x1) × w1+ f (x2) × w2+ f (x3) × w3+ f (x4) × w4, where Y is the second resource allocation value, w1 is the transition weight, w2 is the affinity weight, w3 is the vacancy weight, and w4 is the load weight.
Based on the above description of the embodiments, fig. 3 is a flowchart illustrating another method for allocating worker resources according to an exemplary embodiment of the present application. As shown in fig. 3, the method includes:
s301: receiving historical recruitment data, current task amount and state and/or attribute data of a plurality of candidate brokers, which are sent by at least one business terminal;
s302: determining the conversion degree, the affinity degree, the idleness degree and the load degree of the candidate brokers according to the historical recruitment data, the current task amount and state and/or attribute data of the candidate brokers;
s303: selecting a target broker from the plurality of candidate brokers according to the conversion degrees, the affinity degrees, the idleness degrees and the load degrees of the plurality of candidate brokers;
s304: and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be allocated.
Based on the above description of the embodiments, fig. 4 is a flowchart illustrating another method for allocating worker resources according to an exemplary embodiment of the present application. As shown in fig. 4, the method includes:
s401: receiving historical recruitment data and attribute data of a plurality of candidate brokers sent by at least one business terminal;
s402: determining conversion degrees and affinity degrees of the candidate brokers according to historical recruitment data and attribute data of the candidate brokers, wherein the conversion degrees reflect the capacity of the candidate brokers to recruit workers, and the affinity degrees reflect the affinity degrees of the candidate brokers with the resource data;
s403: selecting a target broker from the plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers;
s404: and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be allocated.
Based on the above description of the embodiments, fig. 5 is a flowchart illustrating another method for allocating worker resources according to an exemplary embodiment of the present application. As shown in fig. 5, the method includes:
s501: receiving current task amount, state and/or attribute data and historical recruitment data of a plurality of candidate brokers, which are sent by at least one business terminal;
s502: determining the idleness and the load degree of the candidate brokers according to the current task amount, the state and/or the attribute data and the historical recruitment data of the candidate brokers, wherein the idleness reflects the waiting time of the candidate brokers for executing new tasks, and the load degree reflects the current task load degree of the candidate brokers;
s503: selecting a target broker from the candidate brokers according to the idleness and the load of the candidate brokers;
s504: and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be allocated.
In the above method embodiments of the present application, the worker resource allocation device receives historical recruitment data, current task volume and status and/or attribute data of a plurality of candidate brokers sent by at least one business terminal; determining resource demand degrees of the candidate brokers according to historical recruitment data, current task amount and state and/or attribute data of the candidate brokers; selecting a target broker from the candidate brokers according to the resource demand degrees of the candidate brokers; and sending the resource data to be distributed to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be distributed, thereby improving the distribution efficiency of tasks and improving the user experience.
It should be noted that the execution subjects of the steps of the methods provided in the above embodiments may be the same device, or different devices may be used as the execution subjects of the methods. For example, the execution subjects of steps 401 to 403 may be device a; for another example, the execution subject of steps 401 and 402 may be device a, and the execution subject of step 403 may be device B; and so on.
In addition, in some of the flows described in the above embodiments and the drawings, a plurality of operations are included in a specific order, but it should be clearly understood that the operations may be executed out of the order presented herein or in parallel, and the sequence numbers of the operations, such as 401, 402, etc., are merely used to distinguish various operations, and the sequence numbers themselves do not represent any execution order. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.
FIG. 6 is a schematic structural diagram of a worker resource allocation device according to an exemplary embodiment of the present disclosure. As shown in fig. 6, the worker resource allocation apparatus includes: a memory 601 and a processor 602. In addition, the worker resource allocation device includes necessary components such as a power component 603 and a communication component 604.
The memory 601, which may be implemented by any type of volatile or non-volatile memory device or combination thereof, may include, for example, Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
A communication component 604 for data transmission with other devices.
Optionally, the processor 602, when determining the conversion degrees and the affinity degrees of the plurality of candidate brokers according to the historical recruitment data and the attribute data of the plurality of candidate brokers, is specifically configured to: determining conversion rates of the candidate brokers according to historical recruitment data of the candidate brokers; calculating conversion scores for the plurality of candidate brokers based on the conversions for the plurality of candidate brokers, the conversion scores for the candidate brokers reflecting the degrees of conversion for the candidate brokers; determining working mode values of the candidate brokers according to the attribute data of the candidate brokers; calculating affinity scores for the plurality of candidate brokers based on the work pattern values for the plurality of candidate brokers, the affinity scores for the candidate brokers reflecting the affinity of the candidate brokers.
Optionally, the processor 602 is specifically configured to, when selecting the target broker from the plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the degrees of affinity of the plurality of candidate brokers: calculating a first resource allocation value for the plurality of candidate brokers based on the conversion scores for the plurality of candidate brokers and the affinity scores for the plurality of candidate brokers; a target broker is selected from a plurality of candidate brokers based on a first resource allocation value of the plurality of candidate brokers.
Optionally, the historical recruitment data includes a total task amount and a conversion success task amount allocated in a unit time, and the processor 602 is specifically configured to, when determining the conversion rates of the candidate brokers according to the historical recruitment data of the candidate brokers: and taking the ratio of the conversion success task amount to the total task amount as the conversion rate of the candidate brokers.
Optionally, the processor 602 may be further configured to: receiving current task volumes and statuses of a plurality of candidate brokers sent by at least one business terminal; determining the idleness and the load degree of the candidate brokers according to the current task amount, the state and/or the attribute data and the historical recruitment data of the candidate brokers, wherein the idleness reflects the waiting time of the candidate brokers for executing new tasks, and the load degree reflects the current task load degree of the candidate brokers; and selecting the target broker from the plurality of candidate brokers according to the conversion degree, the affinity degree, the idleness degree and the load degree of the plurality of candidate brokers.
Optionally, the processor 602 is specifically configured to, when determining the idleness and the load of the candidate brokers according to the current task amount, the status, and/or the attribute data of the candidate brokers and the historical recruitment data,: determining the task interval distribution scores of the candidate brokers according to the current task amount, the state and/or attribute data and the historical recruitment data of the candidate brokers; calculating idleness scores of the candidate brokers according to the assigned task interval scores of the candidate brokers, wherein the idleness scores reflect the idleness of the candidate brokers; determining load rates of the candidate brokers according to current task volumes, states and/or attribute data and historical recruitment data of the candidate brokers; and calculating the load degree scores of the candidate brokers according to the load rates of the candidate brokers, wherein the load degree scores reflect the load degrees of the candidate brokers.
Optionally, the processor 602 is specifically configured to, when determining the load rates of the multiple candidate brokers according to the current task volumes, statuses, and/or attribute data and the historical recruitment data of the multiple candidate brokers: calculating load upper limits of the candidate brokers according to current task volumes, states and/or attribute data and historical recruitment data of the candidate brokers; and calculating the load rates of the candidate brokers according to the load upper limits and the current task amount of the candidate brokers.
Optionally, the processor 602 is specifically configured to, when selecting the target broker from the plurality of candidate brokers according to the conversion degrees, the affinity degrees, the idleness degrees, and the load degrees of the plurality of candidate brokers: calculating a second resource allocation value for the plurality of candidate brokers based on the conversion score, the affinity score, the idleness score, and the load score of the plurality of candidate brokers; a target broker is selected from the plurality of candidate brokers based on the second resource allocation values for the plurality of candidate brokers.
Optionally, the processor 602 is specifically configured to, when calculating the second resource allocation values of the plurality of candidate brokers according to the conversion rate scores, the affinity scores, the idleness scores and the load scores of the plurality of candidate brokers: calculating a second resource allocation value of the plurality of candidate brokers according to the conversion rate score, the affinity score, the idleness score and the load score of the plurality of candidate brokers and the respective weights of the conversion rate score, the affinity score, the idleness score and the load score, wherein the second resource allocation value is calculated by the formula of Y ═ f (x1) × w1+ f (x2) × w2+ f (x3) × w3+ f (x4) × w 4; the conversion rate score is calculated by the formula f (x1) ═ k1 × 1^2+ n 1; the calculation formula of the affinity score is that f (x2) ═ k2 × 2^2+ n 2; the idleness score is calculated by the formula f (x3) ═ k3 × 3+ n 3; the calculation formula of the load score is that f (x4) ═ k4/x4+ n 4;
wherein Y is a second resource allocation value, f (x1) is a conversion rate score, f (x2) is an affinity score, f (x3) is an idleness score, f (x4) is a load score, w1 is a conversion rate weight, w2 is an affinity weight, w3 is an idleness weight, w4 is a load weight, the value ranges of k1, k2, k3 and k4 are (0, 1), n1, n2, n3 and n4 are positive integers, x1 is a conversion rate, x2 is a working mode value, x3 is an allocation task interval score, and x4 is a load rate.
Correspondingly, the embodiment of the application also provides a computer readable storage medium storing the computer program. The computer-readable storage medium stores a computer program, and the computer program, when executed by one or more processors, causes the one or more processors to perform the steps in the method embodiment of fig. 4.
FIG. 7 is a schematic structural diagram of a worker resource allocation device according to an exemplary embodiment of the present application. As shown in fig. 7, the worker resource allocation apparatus includes: a memory 701 and a processor 702. In addition, the worker resource allocation device includes necessary components such as a power component 703 and a communication component 704.
The memory 701 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
A communication component 704 for data transmission with other devices.
Optionally, the processor 702 is specifically configured to, when determining the idleness and the load of the candidate brokers according to the current task amount, the status and/or the attribute data, and the historical recruitment data of the candidate brokers: determining the task interval distribution scores of the candidate brokers according to the current task amount, the state and/or attribute data and the historical recruitment data of the candidate brokers; calculating idleness scores of the candidate brokers according to the assigned task interval scores of the candidate brokers, wherein the idleness scores reflect the idleness of the candidate brokers; determining load rates of the candidate brokers according to current task volumes, states and/or attribute data and historical recruitment data of the candidate brokers; and calculating the load degree scores of the candidate brokers according to the load rates of the candidate brokers, wherein the load degree scores reflect the load degrees of the candidate brokers.
Optionally, the processor 702 is specifically configured to, when selecting the target broker from the plurality of candidate brokers according to the idleness and the load of the plurality of candidate brokers: calculating a first resource allocation value for the plurality of candidate brokers based on the idleness scores of the plurality of candidate brokers and the load scores of the plurality of candidate brokers; a target broker is selected from a plurality of candidate brokers based on a first resource allocation value of the plurality of candidate brokers.
Optionally, the processor 702 may be further configured to: determining conversion degrees and affinity degrees of the candidate brokers according to historical recruitment data and attribute data of the candidate brokers, wherein the conversion degrees reflect the capacity of the candidate brokers to recruit workers, and the affinity degrees reflect the affinity degrees of the candidate brokers with the resource data; and selecting the target broker from the plurality of candidate brokers according to the conversion degree, the affinity degree, the idleness degree and the load degree of the plurality of candidate brokers.
Optionally, the processor 702 is specifically configured to, when determining the conversion degrees and the affinity degrees of the plurality of candidate brokers according to the historical recruitment data and attribute data of the plurality of candidate brokers: determining conversion rates of the candidate brokers according to historical recruitment data of the candidate brokers; calculating conversion scores for the plurality of candidate brokers based on the conversions for the plurality of candidate brokers, the conversion scores for the candidate brokers reflecting the degrees of conversion for the candidate brokers; determining working mode values of the candidate brokers according to the attribute data of the candidate brokers; calculating affinity scores for the plurality of candidate brokers based on the work pattern values for the plurality of candidate brokers, the affinity scores for the candidate brokers reflecting the affinity of the candidate brokers.
Optionally, the historical recruitment data includes a total task amount and a conversion success task amount allocated in a unit time, and the processor 702, when determining the conversion rates of the candidate brokers according to the historical recruitment data of the candidate brokers, is specifically configured to: and taking the ratio of the conversion success task amount to the total task amount as the conversion rate of the candidate brokers.
Optionally, the processor 702 is specifically configured to, when determining the load rates of the multiple candidate brokers according to the current task volumes, statuses, and/or attribute data and the historical recruitment data of the multiple candidate brokers: calculating load upper limits of the candidate brokers according to current task volumes, states and/or attribute data and historical recruitment data of the candidate brokers; and calculating the load rates of the candidate brokers according to the load upper limits and the current task amount of the candidate brokers.
Optionally, the processor 702 is specifically configured to, when selecting the target broker from the plurality of candidate brokers according to the conversion degrees, the affinity degrees, the idleness degrees, and the load degrees of the plurality of candidate brokers: calculating a second resource allocation value for the plurality of candidate brokers based on the conversion score, the affinity score, the idleness score, and the load score of the plurality of candidate brokers; a target broker is selected from the plurality of candidate brokers based on the second resource allocation values for the plurality of candidate brokers.
Optionally, the processor 702 is specifically configured to, when calculating the second resource allocation values of the plurality of candidate brokers according to the conversion rate scores, the affinity scores, the idleness scores and the load scores of the plurality of candidate brokers: calculating a second resource allocation value of the plurality of candidate brokers according to the conversion rate score, the affinity score, the idleness score and the load score of the plurality of candidate brokers and the respective weights of the conversion rate score, the affinity score, the idleness score and the load score, wherein the second resource allocation value is calculated by the formula of Y ═ f (x1) × w1+ f (x2) × w2+ f (x3) × w3+ f (x4) × w 4; the conversion rate score is calculated by the formula f (x1) ═ k1 × 1^2+ n 1; the calculation formula of the affinity score is that f (x2) ═ k2 × 2^2+ n 2; the idleness score is calculated by the formula f (x3) ═ k3 × 3+ n 3; the calculation formula of the load score is that f (x4) ═ k4/x4+ n 4; wherein Y is a second resource allocation value, f (x1) is a conversion rate score, f (x2) is an affinity score, f (x3) is an idleness score, f (x4) is a load score, w1 is a conversion rate weight, w2 is an affinity weight, w3 is an idleness weight, w4 is a load weight, the value ranges of k1, k2, k3 and k4 are (0, 1), n1, n2, n3 and n4 are positive integers, x1 is a conversion rate, x2 is a working mode value, x3 is an allocation task interval score, and x4 is a load rate.
Correspondingly, the embodiment of the application also provides a computer readable storage medium storing the computer program. The computer-readable storage medium stores a computer program, and the computer program, when executed by one or more processors, causes the one or more processors to perform the steps in the method embodiment of fig. 5.
The communication components of fig. 6 and 7 described above are configured to facilitate communication between the device in which the communication component is located and other devices in a wired or wireless manner. The device where the communication component is located can access a wireless network based on a communication standard, such as a WiFi, a 2G, 3G, 4G/LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
The power supply components of fig. 6 and 7 described above provide power to the various components of the device in which the power supply components are located. The power components may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device in which the power component is located.
In the above device embodiment of the present application, the worker resource allocation device receives historical recruitment data, current task volume and status and/or attribute data of multiple candidate brokers sent by at least one business terminal; determining resource demand degrees of the candidate brokers according to historical recruitment data, current task amount and state and/or attribute data of the candidate brokers; selecting a target broker from the candidate brokers according to the resource demand degrees of the candidate brokers; and sending the resource data to be distributed to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting workers according to the resource data to be distributed, thereby improving the distribution efficiency of tasks and improving the user experience.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (11)
1. A method for worker resource allocation, comprising:
receiving historical recruitment data and attribute data of a plurality of candidate brokers sent by at least one business terminal;
determining a degree of conversion and a degree of affinity of the plurality of candidate brokers according to historical recruitment data and attribute data of the plurality of candidate brokers, wherein the degree of conversion reflects the ability of the candidate brokers to recruit workers and the degree of affinity reflects the degree of affinity of the candidate brokers with the resource data;
selecting a target broker from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers;
and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting the laborers according to the resource data to be allocated.
2. The method of claim 1, wherein determining a degree of conversion and a degree of affinity for the plurality of candidate brokers based on historical recruitment data and attribute data for the plurality of candidate brokers comprises:
determining conversion rates for the plurality of candidate brokers based on historical recruitment data for the plurality of candidate brokers; calculating conversion scores for a plurality of candidate brokers based on the conversions for the plurality of candidate brokers, the conversion scores for the candidate brokers reflecting the degrees of conversion for the candidate brokers;
and
determining an operating mode value of the plurality of candidate brokers according to the attribute data of the plurality of candidate brokers; calculating affinity scores for the plurality of candidate brokers based on the work pattern values for the plurality of candidate brokers, the affinity scores for the candidate brokers reflecting the affinity of the candidate brokers.
3. The method of claim 2, wherein selecting a target broker from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers comprises:
calculating a first resource allocation value for the plurality of candidate brokers based on the conversion scores for the plurality of candidate brokers and the affinity scores for the plurality of candidate brokers;
selecting a target broker from a plurality of candidate brokers based on the first resource allocation values of the plurality of candidate brokers.
4. The method of claim 2, wherein the historical recruitment data includes a total volume of tasks allocated per unit of time and a volume of conversion success tasks, and wherein determining the conversion rates for the plurality of candidate brokers based on the historical recruitment data for the plurality of candidate brokers comprises:
and taking the ratio of the conversion success task amount to the total task amount as the conversion rate of the candidate brokers.
5. The method of claim 2, further comprising:
receiving current task volumes and statuses of a plurality of candidate brokers sent by at least one business terminal;
determining the idleness and the load degree of a plurality of candidate brokers according to the current task amount, state and/or attribute data and historical recruitment data of the candidate brokers, wherein the idleness reflects the waiting time of the candidate brokers for executing new tasks, and the load degree reflects the current task load degree of the candidate brokers;
selecting a target broker from a plurality of candidate brokers based on the conversions, affinities, idleness, and load of the plurality of candidate brokers.
6. The method of claim 5, wherein determining idleness and load of a plurality of candidate brokers based on current mission volume, status and/or attribute data, historical recruitment data for the plurality of candidate brokers comprises:
determining assigned mission interval scores of a plurality of candidate brokers according to current mission volume, status and/or attribute data, historical recruitment data of the plurality of candidate brokers; calculating idleness scores of the plurality of candidate brokers according to the assigned task interval scores of the plurality of candidate brokers, wherein the idleness scores reflect idleness of the candidate brokers;
and the number of the first and second groups,
determining load rates of a plurality of candidate brokers according to current task volumes, status and/or attribute data and historical recruitment data of the candidate brokers; calculating load degree scores of the candidate brokers according to the load rates of the candidate brokers, wherein the load degree scores reflect the load degrees of the candidate brokers.
7. The method of claim 6, wherein determining load rates for a plurality of candidate brokers based on current mission volume, status, and/or attribute data, historical recruitment data for the plurality of candidate brokers comprises:
calculating load upper limits of the candidate brokers according to current task volumes, states and/or attribute data and historical recruitment data of the candidate brokers;
and calculating the load rates of the candidate brokers according to the load upper limits and the current task amount of the candidate brokers.
8. The method of claim 6, wherein selecting a target broker from a plurality of candidate brokers based on the conversions, affinities, idleness, and load of the plurality of candidate brokers comprises:
calculating a second resource allocation value for the plurality of candidate brokers based on the conversion score, affinity score, idleness score, and load score of the plurality of candidate brokers;
selecting a target broker from a plurality of candidate brokers based on second resource allocation values for the plurality of candidate brokers.
9. The method of claim 8, wherein calculating a second resource allocation value for the plurality of candidate brokers based on the conversion scores, affinity scores, idleness scores, and load scores of the plurality of candidate brokers comprises:
calculating a second resource allocation value of the candidate brokers according to the conversion rate score, the affinity score, the idleness score and the load score of the candidate brokers and the respective weights of the conversion rate score, the affinity score, the idleness score and the load score, wherein the second resource allocation value is calculated by the formula of Y ═ f (x1) × w1+ f (x2) × w2+ f (x3) × w3+ f (x4) × w 4;
the conversion rate score is calculated by the formula f (x1) ═ k1 × 1^2+ n 1;
the calculation formula of the affinity score is that f (x2) ═ k2 × 2^2+ n 2;
the idleness score is calculated by the formula f (x3) ═ k3 × 3+ n 3;
the calculation formula of the load score is that f (x4) ═ k4/x4+ n 4;
wherein Y is a second resource allocation value, f (x1) is a conversion rate score, f (x2) is an affinity score, f (x3) is an idleness score, f (x4) is a load score, w1 is a conversion rate weight, w2 is an affinity weight, w3 is an idleness weight, w4 is a load weight, the value ranges of k1, k2, k3 and k4 are (0, 1), n1, n2, n3 and n4 are positive integers, x1 is a conversion rate, x2 is a working mode value, x3 is an allocation task interval score, and x4 is a load rate.
10. A worker resource allocation apparatus, comprising: a memory, a processor, and a communication component;
the memory for storing a computer program;
the communication component is used for establishing communication connection with other equipment;
the processor to execute the computer program to:
receiving, by a communication component, historical recruitment data and attribute data of a plurality of candidate brokers transmitted by at least one business terminal;
determining a degree of conversion and a degree of affinity of the plurality of candidate brokers according to historical recruitment data and attribute data of the plurality of candidate brokers, wherein the degree of conversion reflects the ability of the candidate brokers to recruit workers and the degree of affinity reflects the degree of affinity of the candidate brokers with the resource data;
selecting a target broker from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers;
and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting the laborers according to the resource data to be allocated.
11. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by one or more processors, causes the one or more processors to perform acts comprising:
receiving historical recruitment data and attribute data of a plurality of candidate brokers sent by at least one business terminal;
determining a degree of conversion and a degree of affinity of the plurality of candidate brokers according to historical recruitment data and attribute data of the plurality of candidate brokers, wherein the degree of conversion reflects the ability of the candidate brokers to recruit workers and the degree of affinity reflects the degree of affinity of the candidate brokers with the resource data;
selecting a target broker from a plurality of candidate brokers based on the degrees of conversion of the plurality of candidate brokers and the affinities of the plurality of candidate brokers;
and sending the resource data to be allocated to the terminal equipment used by the target broker so that the target broker executes the operation of recruiting the laborers according to the resource data to be allocated.
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| CN113570258A (en) * | 2021-07-30 | 2021-10-29 | 北京房江湖科技有限公司 | Task allocation method and computer program product |
| CN113570258B (en) * | 2021-07-30 | 2024-04-12 | 贝壳找房(北京)科技有限公司 | Task allocation method and computer program product |
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