CN111445053A - Employment demand information processing method and device and electronic equipment - Google Patents
Employment demand information processing method and device and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application discloses an employment requirement information processing method, a device and electronic equipment, wherein the method comprises the following steps: acquiring the recruitment requirement prediction information in the target time period; providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations; and adding a corresponding visual operation object in the first visual chart according to the selected recruitment hierarchy, so that the similarity between the combined second visual chart and the first visual chart meets a preset condition by combining the visual operation objects corresponding to a plurality of different recruitment hierarchies. Through the embodiment of the application, the visual configuration of the employment requirement can be realized while the cost is reduced and the efficiency is improved through the employment layering, and the result of the configuration is more easily close to the predicted value.
Description
Technical Field
The present application relates to the field of labor demand information processing technologies, and in particular, to a method and an apparatus for processing labor demand information, and an electronic device.
Background
Crowdsourcing refers to the act of a company or institution outsourcing work tasks that have been performed by employees to unspecified (and often large) masses in a voluntary fashion to complete, the company or institution settling the masses for payroll on an hourly basis. For example, in a "new retail" business model, the distribution tasks of the distribution stations may be outsourced to the general public by crowd sourcing.
In practical applications, because the total task amount per day may be different, an administrator of an employment party (e.g., a distribution station, etc.) is usually required to issue an employment requirement per day, determine specific employment time and the employment amount, and the public can obtain corresponding work in a task-grabbing manner according to the time of the public and the like. In order to accurately release the labor demand, the labor amount required in each time period in a day can be generally predicted according to information such as specific single amount, for example, 8 people are required from 6 to 7, 8 people are required from 7 to 8, 12 people are required from 8 to 9, the labor peak is generated from 9 to 10, 58 people are required, and the like. In summary, with such a prediction system, the amount of labor required per hour can be predicted relatively accurately.
If the cost problem is not considered, the recruitment requirement is issued only according to the prediction result, namely, the recruitment requirement is issued according to the corresponding predicted recruitment quantity per hour. However, in practical applications, this approach may result in a relatively high labor cost. Specifically, to encourage more people to be willing to undertake work at peak hours, the labor price at peak hours may be relatively high, e.g., 6 dollars per hour during off-peak hours, 8 dollars per hour during peak hours, etc. If the release of employment requirements is made directly in terms of the number of workers per hour, this results in the need for 8 dollar per hour compensation by all those working during peak hours. In addition, if the release of labor demand is performed in units of hours, the following problems may occur: the same "rider" can provide service for a longer time in the same day, but the actual task may not be continuous in time, for example, a certain "rider" may get 6 o 'clock to 7 o' clock in a certain day, 7 o 'clock to 8 o' clock may not get, and then get 8 o 'clock to 9 o' clock. At this time, the "rider" needs to wait within the hour from 7 o 'clock to 8 o' clock, which inevitably affects participation enthusiasm of the "rider", and in addition, for the system, rewards obtained when the same "rider" performs tasks in different time periods in the same day may be different, and payments for paying fees for the same "rider" need to be performed for different time periods respectively, which obviously also brings more workload for the system, affects efficiency, and has higher cost.
Disclosure of Invention
The application provides an employment demand information processing method and device and electronic equipment, which can realize visual configuration of employment demands while reducing cost and improving efficiency through employment layering, and enable configuration results to be close to predicted values more easily.
The application provides the following scheme:
a labor demand information processing method comprises the following steps:
acquiring the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations, and the continuous employment durations comprise a plurality of continuous unit time periods;
and adding a corresponding visual operation object in the first visual chart according to the selected recruitment hierarchy, so that the similarity between the combined second visual chart and the first visual chart meets a preset condition by combining the visual operation objects corresponding to a plurality of different recruitment hierarchies.
A labor demand information processing method comprises the following steps:
receiving recruitment requirement issuing request information submitted by a client, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and the similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and issuing the employment demand.
A labor demand information processing method comprises the following steps:
receiving recruitment requirement information, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment layering information, and the similarity between the combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and providing operation options for picking up the tasks corresponding to the employment demands so as to pick up the tasks by taking the employment hierarchies as units.
A labor demand information processing method comprises the following steps:
acquiring recruitment requirement prediction information in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the number of recruitment required prediction results corresponding to the unit time periods;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; the recruitment duration corresponding to the same continuous recruitment category comprises a plurality of continuous unit time periods.
A labor demand information processing method comprises the following steps:
acquiring recruitment demand prediction information of an operator in a target entity shop within a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the prediction result information of the required recruitment number corresponding to each unit time period;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; and the continuous recruitment time length corresponding to the same recruitment type comprises a plurality of continuous unit time periods.
A method for processing labor demand information of a robot comprises the following steps:
acquiring recruitment requirement prediction information of the robot in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the required recruitment quantity prediction result information corresponding to the unit time periods respectively;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; and the continuous recruitment time length corresponding to the same recruitment type comprises a plurality of continuous unit time periods.
A vehicle demand information processing method comprising:
acquiring recruitment demand prediction information of a vehicle in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the required recruitment number prediction results corresponding to the unit time periods;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; and the continuous recruitment time length corresponding to the same recruitment type comprises a plurality of continuous unit time periods.
An employment requirement information processing apparatus comprising:
the prediction information obtaining unit is used for obtaining the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
the configuration interface providing unit is used for providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations; the continuous labor duration comprises a plurality of continuous unit time periods;
and the visual operation object combination unit is used for adding corresponding visual operation objects in the histogram according to the selected recruitment hierarchy so as to combine the visual operation objects corresponding to a plurality of different recruitment hierarchies to ensure that the similarity of the combined second visual chart and the first visual chart meets a preset condition.
An employment requirement information processing apparatus comprising:
the system comprises a release request receiving unit, a processing unit and a processing unit, wherein the release request receiving unit is used for receiving recruitment requirement release request information submitted by a client, the recruitment requirement information is obtained by combining visual operation objects corresponding to various optional recruitment hierarchical information, and the similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and the recruitment requirement issuing unit is used for issuing the recruitment requirement.
An employment requirement information processing apparatus comprising:
the recruitment requirement receiving unit is used for receiving recruitment requirement information, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and the similarity between the combined second visual chart and a first visual icon corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and the operation option providing unit is used for providing operation options for picking up the tasks corresponding to the employment requirements so as to pick up the tasks by taking the employment hierarchy as a unit.
An employment requirement information processing apparatus comprising:
the system comprises a prediction information obtaining unit, a prediction information obtaining unit and a processing unit, wherein the prediction information obtaining unit is used for obtaining recruitment requirement prediction information in a target time period, the target time period comprises a plurality of unit time periods, and the prediction information comprises required recruitment quantity prediction result information corresponding to the unit time periods respectively;
the demand layering processing unit is used for classifying the employment demands according to the distribution condition of the employment quantity information corresponding to each unit time period in the employment demand prediction information so as to determine continuous employment duration information corresponding to at least one employment category and start-stop time and employment quantity information of each employment category; and the continuous recruitment time length corresponding to the same recruitment type comprises a plurality of continuous unit time periods.
An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
acquiring the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations, and the continuous employment durations comprise a plurality of continuous unit time periods;
and adding corresponding visual operation objects in the histogram according to the selected recruitment hierarchy, so that the similarity between the combined second visual chart and the first visual chart meets a preset condition by combining the visual operation objects corresponding to a plurality of different recruitment hierarchies.
An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
receiving recruitment requirement issuing request information submitted by a client, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and the similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and issuing the employment demand.
An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
receiving recruitment requirement information, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment layering information, and the similarity between the combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and providing operation options for picking up the tasks corresponding to the employment demands so as to pick up the tasks by taking the employment hierarchies as units.
An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
acquiring recruitment requirement prediction information in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the number of recruitment required prediction results corresponding to the unit time periods;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; and the continuous recruitment time length corresponding to the same recruitment hierarchy comprises a plurality of continuous unit time periods.
According to the specific embodiments provided herein, the present application discloses the following technical effects:
through this application embodiment, can carry out the issue of recruitment demand through the mode of recruitment layering, different layering can correspond different continuous with the worker time length, like this, specific manpower resources user can be after receiving with specific demand information, can get specific task according to specific recruitment layering to provide the operation service in the time length of corresponding recruitment, consequently, can play reduce cost, raise the effect of efficiency. Meanwhile, a histogram corresponding to the recruitment requirement prediction result can be displayed in the recruitment requirement information configuration interface, and a corresponding visual operation object can be provided for a specific recruitment hierarchy. Therefore, the embodiment of the application can more effectively issue the employment requirement, the cost is reduced, the visual configuration of the employment requirement is realized, and the configuration result is more easily close to the predicted value.
Of course, it is not necessary for any product to achieve all of the above-described advantages at the same time for the practice of the present application.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a schematic diagram of a system architecture provided by an embodiment of the present application;
FIG. 2 is a flow chart of a first method provided by an embodiment of the present application;
3-1 through 3-3 are schematic diagrams of configuration interfaces provided by embodiments of the present application;
FIG. 4 is a flow chart of a second method provided by embodiments of the present application;
FIG. 5 is a flow chart of a third method provided by embodiments of the present application;
FIG. 6 is a flow chart of a fourth method provided by embodiments of the present application;
FIG. 7 is a schematic diagram of a first apparatus provided by an embodiment of the present application;
FIG. 8 is a schematic diagram of a second apparatus provided by an embodiment of the present application;
FIG. 9 is a schematic diagram of a third apparatus provided by an embodiment of the present application;
FIG. 10 is a schematic diagram of a fourth apparatus provided by an embodiment of the present application;
fig. 11 is a schematic diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments that can be derived from the embodiments given herein by a person of ordinary skill in the art are intended to be within the scope of the present disclosure.
It should be noted that, for the problem existing when the recruitment requirement is issued in hours, some "crowdsourcing" platforms propose a method of determining the total time of the recruitment according to the duration of the recruitment, that is, specific rewards are not calculated according to different time points in the same day, and are not determined according to whether the corresponding rewards are peak hours of the recruitment or not, but according to the working duration in the same day, for example, if the work can be continuously performed for 12 hours, 6.2 dollars per hour, if the work can be continuously performed for 6 hours, 6.8 dollars per hour, if the work can be continuously performed for 2 hours, 7.6 dollars per hour, and so on, the general workforce can perform the task according to the working duration which can be provided in the same day when the task is taken, for example, if a user a has more idle time in a day than the working duration, the task with working duration of 12 hours can be taken, after the task is completed, the obtained 6.2 dollars 83, 74.8 dollars are not necessarily equal to the total working duration of 6 dollars, so that the user can easily take the total working duration of the same working time when the task is not completed, and the task is no longer performed for the same time when the task, so that the user a working duration is not completed task, the user B may not performed for 6 dollars, and the user B is equal working duration, so that the working duration, the user can easily perform the total working duration of the task when the working duration of the same working duration, the working duration is equal working duration, the working duration of the working duration, the working duration is not more than the working duration, and the working duration of the working duration, and the working duration is equal working duration of the working duration, the working duration of the working hours, the working duration of the working hours, and the working duration of the working hours, the working.
That is, the employment layers can be implemented according to different employment durations, but in the process of implementing the above scheme, the problem of how to distribute each employment layer needs to be solved. This is because each employment layer only corresponds to the time length information of employment, but the amount of employment of each layer is configured according to the actual requirement from when each employment layer starts to when each employment layer ends. In specific implementation, as described above, the system can predict the number of workers per hour according to the information such as the daily single quantity, so that the starting and ending time points of various worker hierarchies and the corresponding number of workers are reasonably configured to be as close as possible to the prediction result of the number of workers of the system.
In order to achieve the above purpose, in the prior art, a user of a worker administrator is usually required to fill in the starting and ending time of various worker hierarchies and the corresponding number of workers by means of a tool such as an electronic form, then, a histogram (the abscissa is time, and the ordinate is number of workers) is generated by using an icon function provided by the electronic form tool, then, the generated histogram is compared with a histogram corresponding to a predicted value result of the number of workers obtained before the system, and if the two are close to each other, the worker requirement can be issued according to the current configuration result; and if the two are not close enough and need to be modified, returning to a specific spreadsheet editing interface, modifying the numerical value of each field again, wherein the numerical value comprises the starting time corresponding to each employment layer, the amount of the employment and the like, after the modification is finished, regenerating the histogram, comparing the histogram with the prediction result histogram, judging whether the proximity degree between the two meets the requirement, and the like.
In the above manner, since the histogram needs to be generated after the specific numerical values are configured in the spreadsheet each time, and then the comparison is performed, specifically, when the numerical values are configured, no intuitive information can be referred to, only rough configuration can be performed first, and after one configuration is completed, the histogram is clicked to generate and then compared with the predicted value histogram, and then the direction of the optimal adjustment can be determined, including whether the start time of a certain employment level, the amount of employment, and the like need to be adjusted. Therefore, the process of configuring through the 'pieced together' numerical value needs to be repeatedly modified for many times, and needs to be switched back and forth between a form editing interface and a histogram display interface, so that the configuration efficiency is low.
In view of the above problems, embodiments of the present application provide a corresponding solution. In the scheme, an implementation mode for carrying out visual configuration on the employment requirement is provided. Specifically, the scheme can firstly display a histogram of the recruitment requirement prediction information in the configuration interface, wherein the histogram takes time as an abscissa and takes the recruitment number as an ordinate. In the prediction information histogram, the information of the number of workers per unit time period (for example, one time unit per hour) is represented, for example, 6 o 'clock to 7 o' clock and 8 people, 7 o 'clock to 8 o' clock and 8 o 'clock to 9 o' clock and 12 people, 9 o 'clock to 10 o' clock and 58 people, and the like. In addition, operation options corresponding to multiple employment hierarchies can be provided in the interface, wherein each employment hierarchy can correspond to a certain number of visual objects, and the visual objects can also have a columnar shape, the width of the visual objects is fixed and cannot be adjusted, and the width of the visual objects corresponds to the duration of the employment corresponding to a specific employment hierarchy; the height of the visual object represents the corresponding amount of the recruitment and can be adjusted, and in addition, the specific visual object can also move left and right on the abscissa so as to adjust the starting time of the specific recruitment layer. Like this, because the recruitment duration that different recruitment layers correspond is different, consequently, different recruitment layers will correspond the visual object of different width, through the position to the visual object of various different widths in the histogram coordinate system to and the regulation of height, can realize through the mode similar to "take the building blocks", realize the visual configuration to specific recruitment demand.
In specific implementation, from the perspective of system architecture, as shown in fig. 1, the embodiment of the present application may provide a system for publishing employment demands, where the system may include a server, and the specific user may be a distribution station, an entity store, and other users who need to publish the employment demands in a "crowdsourcing" manner, such as a station leader, a store leader, and the like. In order to facilitate the user to obtain the corresponding service, a client may be provided for the user, and the client may exist in the form of an independent application program or may also exist in the form of a web page. For the former, a user may install a relevant application program in a mobile terminal device, a PC, or other devices, so as to obtain a relevant configuration interface and perform human-computer interaction. For the latter, the server initiates access to a webpage provided by a server through terminal equipment such as a PC and the like, and can log in by using information such as a pre-registered account, the server confirms the identity of the user according to the information such as a specific account, including the identification of a related distribution station and an entity shop, and then can provide corresponding information in a specific configuration interface so as to configure and release the employment requirement.
The following describes in detail specific implementations provided in embodiments of the present application.
Example one
First, in the first embodiment, from the perspective of the client provided for the specific employment requirement issuing user, a method for processing employment requirement information is provided, and referring to fig. 2, the method may specifically include:
s201: acquiring the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
the specific employment requirement prediction information may be obtained by a specific prediction algorithm and the like. The labor demand prediction information may be specifically expressed according to the number of workers per hour. For example, as shown in fig. 2-1, may include 6: 00-7: number of labor required 00, 7: 00-8: 00, etc. However, in the embodiment of the present application, when the user request is specifically issued, the user request is issued not in units of the above-described number of workers per hour, but in accordance with the preset worker hierarchy information.
In the specific implementation, the specific manner of forecasting the employment requirement may be different according to different application scenarios. For example, in a scenario of employment in a physical store combined online and offline, the physical store may need to receive an order from an online customer user, perform operations such as processing, packaging, and the like in the physical store, and then deliver the order to a delivery address specified by the user in as short a time as possible. For example, there may be only a half hour between the order of the user and the delivery completion, etc. However, during times of heavy activities and the like, particularly during times of peak hours of eating and the like, since a large number of orders are concurrently placed, there is a possibility that the manpower resources owned by the entity stores are insufficient. In this case, some social human resources can be recruited in the form of "crowdsourcing" and the like by releasing the labor demand information, and the human resources can be used for supplementing the human resources owned by the entity shop, so that the processing, making, distribution and the like of the orders can be guaranteed to be completed in a short time within a time period when the orders are massively concurrent.
In this case, specifically, when forecasting the employment demand, the total amount of human resources required may be forecasted first according to the information of the number of orders to be processed in the target time period in the target entity store. The information of the number of orders to be processed in the target time period may be estimated according to historical experience and the like. In the case that the total amount of the required human resources is predicted, the amount information of the available human resources when the target entity store is laid in the target time period, for example, how many human resources are owned in the target entity store, and the like, may also be determined. Then, the labor demand prediction information in the target time period can be obtained according to the amount information of the self human resources and the total amount of the required human resources. The work types involved in a specific entity shop may be various, for example, including a cutting member, a packing member, a cook, a delivery member, and the like, so that prediction can be performed for each work type, specifically when prediction is performed.
S202: providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations, and the continuous employment durations comprise a plurality of continuous unit time periods;
in the embodiment of the application, after the specific labor demand prediction information is determined, a labor demand configuration interface may be provided, and a first visual chart corresponding to the prediction information is provided in the configuration interface, as shown at 301 in fig. 3-1, and may specifically exist in the form of a histogram or the like. The histogram comprises a first coordinate axis and a second coordinate axis, wherein the first coordinate axis corresponds to time information, and the second coordinate axis corresponds to people number information. In addition, a variety of optional employment level information may also be included in the configuration interface, as shown at 302 in FIG. 3-1. That is to say, in the embodiment of the present application, a visual labor requirement configuration manner is provided, and a specific configuration process may be completed by performing an operation on the histogram corresponding to the prediction information.
In a specific implementation manner, in order to better adapt to a histogram, the visual operation object may also be specifically represented as a rectangular block, where the rectangular block has a default width value in a first coordinate axis direction and a default height value in a second coordinate axis direction; the width value is continuous recruitment duration information corresponding to the recruitment hierarchy, the height value corresponds to the recruitment number corresponding to the recruitment hierarchy, and when the prediction result corresponds to the histogram, the starting and ending time of recruitment corresponding to the position of the visual operation object in the direction of the first coordinate axis is set. It should be noted that, since the length of the labor time corresponding to the labor hierarchy is usually greater than one hour, the width of the block corresponding to each labor hierarchy is usually greater than the width of each block in the histogram corresponding to the specific prediction result.
In particular, in order to avoid misuse of the employment hierarchy, the number of the visual operation objects corresponding to the same employment hierarchy may be limited, for example, 1 object corresponding to 12 hours, two objects corresponding to 6 hours, two objects corresponding to 2 hours, and the like. Specific users can combine results which are as consistent as possible with the recruitment requirement prediction information by reasonably distributing the starting and ending time, the recruitment number and the like corresponding to various recruitment hierarchies.
S203: and adding a corresponding visual operation object on the basis of the first visual chart according to the selected employment hierarchy, so that the similarity between the combined second visual chart and the first visual chart meets the preset condition by combining the visual operation objects corresponding to a plurality of different employment hierarchies.
After one specific employment layer is selected, a corresponding visual operation object can be added in the employment demand prediction result histogram. In a specific implementation, for example, as shown in fig. 3-2, such a visual operation object may have a translucent characteristic, so that while the visual operation object is displayed, a histogram corresponding to a prediction result of a lower layer may be viewed, so as to enable an intuitive adjustment. After a specific visual operation object is added into the histogram, the width value of the rectangular block is a fixed value, and the height value and the position in the first coordinate axis direction are adjustable. That is, in the example shown in fig. 3-2, the rectangular blocks corresponding to the specific labor level can be adjusted in left and right positions or expanded and contracted in height. The left-right adjustment refers to dragging and adjusting the visual operation object to the left or right along the direction of the transverse coordinate axis as a whole to adjust the corresponding work starting time and the corresponding work ending time, but the width of the specific visual operation object is not changed, that is, the time interval from the starting time to the ending time is not changed and is always consistent with the corresponding work duration. For example, in the initial state, for a recruitment hierarchy corresponding to a 12-hour recruitment duration, after it is selected, the corresponding visualization operation object may default to appear from 6: 00 to 18: 00, but, depending on the prediction of specific employment requirements, may vary from 7: 00 start to 19: 00 ends more appropriately, so it can be dragged right to 7: the position corresponding to time 00, and so on. The height adjustment is specifically to vertically extend and retract the height of a specific visual operation object along the direction of the longitudinal coordinate axis, so that the specific amount of labor under the labor hierarchy can be adjusted. For example, also for the above-mentioned 12-hour labor intensity, after it is selected, the number of people corresponding to the height of the corresponding visual operation object may be 10 people, but it is found by observing the histogram of the prediction result of the specific labor demand that the number of people of the labor intensity is 15, it is easier to combine a scheme closer to the prediction result with other labor intensity, and therefore, the visual operation object can be stretched upward in the longitudinal direction, and accordingly, the number of workers corresponding to the labor intensity can be increased, and so on.
During specific implementation, in order to facilitate operation, the visual operation object corresponding to the longest work duration can be preferentially added to the first visual chart, and the visual operation object added later can be placed on the left side, the right side or the upper side of the visual operation object added earlier, and no gap exists between the visual operation object and the visual operation object. Of course, in practical applications, in most cases, the visualization operation object corresponding to the short labor duration appears above the longer visualization operation object, for example, as shown in fig. 3-3, 8: 00 to 20: 00, a first visual operation object corresponding to the 12-hour period of labor is placed, and in addition, 9: 00 to 11: 00, an employment peak appears, so that a third visual operation object with two hours of employment time can be placed above the first visual operation object; 13: 00 to 19: 00 has a peak time duration, from 16: 00 to 18: 00 is also exceptionally labor intensive, so first one can first place over the first visual manipulation object, 13: 00 to 19: 00, placing a second visual operation object with the labor duration of six hours, and then, above the second visual operation object, 16: 00 to 18: 00, a third visual operation object with the labor duration of two hours is placed. Therefore, in the scheme, a first visual operation object with 12-hour labor duration, a second visual operation object with four-hour labor duration and a third visual operation object with two-hour labor duration are used, and through the four visual operation objects, the operation is more visually performed in a form similar to a 'building block', so that the specific histogram effect can be checked in real time in the operation process, and the observation mode can be directly compared with the histogram corresponding to the prediction information, thereby facilitating the visual adjustment of specific labor layering, specific labor starting time, the labor amount and the like.
In an optional embodiment, the configuration interface may further include a data table, as shown in fig. 3 to 3, and the start-stop time information and the labor amount information of the corresponding labor hierarchy may be added to the data table according to the operation result of the visual operation object. For example, when a first visual operand is added and the start time is adjusted to 8 by dragging the operand: 00, the specific amount of employment is adjusted to 20 people by longitudinally stretching the visual operation object, and then the employment layering information, the employment duration information, the employment time interval information, the employment amount information, and the like corresponding to the first visual operation object can be displayed in the data table below the specific configuration interface. In addition, in an alternative mode, an option for configuring information such as unit price (that is, reward information to be paid per hour) corresponding to each employment hierarchy may be displayed, the unit price may be configured directly in the table, and the configuration may be issued directly after completion of the configuration. For example, the following may be specifically mentioned in table 1:
TABLE 1
By working layers | Duration of employment | Period of employment | Amount of labor | Univalent (yuan) |
A layer of | 12 hours | 8:00~20:00 | 22 | 6.2 |
Two |
6 hours | 13:00~19:00 | 23 | 6.8 |
Three |
2 hours | 9:00~11:00 | 32 | 7.6 |
Three |
2 hours | 16:00~18:00 | 11 | 7.6 |
That is to say, in the embodiment of the present application, in the process of operating and adjusting the visual operation objects corresponding to various hierarchies in the form of "building blocks", the data in the data table below may be automatically generated, and the user is not required to perform manual input.
In addition, an operation option for issuing the employment requirement can be provided in the configuration interface, so that after the specific configuration is completed, an operation instruction can be received through the operation option, and the employment requirement information obtained by combining the visual operation objects is issued.
In a word, according to the embodiment of the application, the histogram corresponding to the employment requirement prediction result can be displayed in the configuration interface, and the corresponding visual operation object can be provided for the specific employment hierarchy, so that the specific employment requirement configuration information can be made to approach the employment requirement prediction result as much as possible by combining the visual operation objects corresponding to a plurality of different employment hierarchies and the like. Therefore, the visual configuration of the employment requirement can be realized in the embodiment of the application, and the configuration result is more easily close to the predicted value.
Example two
The second embodiment provides a method for processing labor demand information from the perspective of a server, and referring to fig. 4, the method may specifically include:
s401: receiving recruitment requirement issuing request information submitted by a client, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and the similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
s402: and issuing the employment demand.
EXAMPLE III
In a third embodiment, from the perspective of a client provided for a labor force user, a labor demand information processing method is provided, and referring to fig. 5, the method may specifically include:
s501: receiving recruitment requirement information, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment layering information, and the similarity between the combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
s502: and providing operation options for picking up the tasks corresponding to the employment demands so as to pick up the tasks by taking the employment hierarchies as units.
That is to say, after the information such as the number of workers and the time period corresponding to various labor levels is released according to the configuration manner in the first embodiment, the specific labor demand information may be sent to the client of the labor user, the labor user may view the specific demand information through the client, and may select a task suitable for the labor user to pick up, and then report the information according to the corresponding labor location and provide the corresponding work service.
For the parts of the second embodiment and the third embodiment that are not described in detail, reference may be made to the descriptions of the first embodiment, and details are not repeated here.
Example four
In the foregoing embodiments, information such as continuous employment duration information corresponding to various employment hierarchies and selectable times of each employment hierarchy is configured in advance in the system, a specific visual operation object is provided for a specific demand publisher user, and the demand publisher user configures and publishes the employment demand in a manual configuration manner. That is, the size and number of each block are predefined, and the user can only select and combine the configuration results as close to the predicted values as possible from the blocks. In the fourth embodiment, the predicted results of the number of workers per promotion activity may be different, and the specific distribution of the number of workers per unit time period may also be different, so that the manner of providing the "building blocks" with the size and the number in advance may not be able to cope with various changes of the specific predicted results. Therefore, in the fourth embodiment, according to the specific result of the forecast of the employment requirement, an automated process of the employment hierarchy may be performed, that is, how many work hierarchies (blocks) are specifically needed, and the duration (size) of continuous employment, the start-stop time, and the amount of employment corresponding to each of the plurality of work hierarchies may be automatically determined according to the result of the forecast of the amount of employment corresponding to each of the plurality of unit time periods. Specifically, referring to fig. 6, a fourth embodiment specifically provides a labor demand information processing method, which may specifically include:
s601: acquiring recruitment requirement prediction information in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the number of recruitment required prediction results corresponding to the unit time periods;
s602: according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment hierarchy, and the start-stop time and the recruitment number information of each recruitment category; the recruitment duration corresponding to the same continuous recruitment category comprises a plurality of continuous unit time periods.
In particular, there may be various ways to perform the automatic classification of the employment requirement. For example, in one mode, the employment quantity prediction result may be compared with each other in a plurality of consecutive unit time periods in which the employment quantity prediction result is greater than a preset threshold value. The screening step is performed because the specific prediction result may include some time periods with very small employment requirement, such as some early morning hours, and the like, the order amount of these time periods is usually small, and the operator in the general employment unit can handle the time periods, and therefore, the time periods may not be within the consideration range of the employment requirement. In addition, since the time of day generally generates a large amount of labor demand as orders are generated, the unit time periods with large demand are generally continuous, for example, from eight morning hours to 20 evening: 00, and so on. After the unit time periods are selected, the results of the prediction of the amount of labor corresponding to the time periods can be compared pairwise, and then the unit time periods can be divided into a plurality of groups according to the results of pairwise comparison. For example, a threshold may be preset, and if the difference between the work quantity prediction results corresponding to two unit time periods is less than or equal to the threshold, the two unit time periods may be classified into the same group, otherwise, the two unit time periods may be classified into different groups.
For example, assume that in a unit time period of one hour, the unit time period is screened from 8: 00 to 20: these 12 hours between 00. Wherein, the concrete prediction results comprise:
according to the difference between the prediction results of the number of used workers corresponding to each unit time period, the prediction results can be divided into the following groups:
a first group: 8: 00-9: 00, 11: 00-12: 00, 12: 00-13: 00, 19: 00-20: 00
Second group: 13: 00-14: 00, 14: 00-15: 00, 15: 00-16: 00, 18: 00-19: 00
Third group: 9: 00-10: 00, 10: -11: 00
And a fourth group: 16: 00-17: 00, 17: 00-18: 00
It should be noted that, specifically, when determining the group information, the problem of the number of unit time periods included in the same group may also be considered, and generally, no less than two unit time periods are included in the same group, so as to achieve the purpose of labor stratification.
After the grouping result is obtained, the recruitment classification can be performed according to the unit time period in each group and the corresponding recruitment number prediction result.
Specifically, the continuous recruitment duration and the start-stop time point of the corresponding recruitment category can be determined according to the maximum time span between unit time periods in the same group; for example, for the first group mentioned above, the earliest is 8: 00-9: 00, 19 at the latest: -20: 00, the time span is 12 hours, so the continuous employment duration corresponding to the employment category can be determined as 12 hours. At the same time, it can be determined that the starting time of the employment category is 8: 00, end time 20: 00. for the second group mentioned above, the earliest is 13: 00-14: 00, latest 18: 19. about.19: 00, the time span is 6 hours, so the continuous employment duration corresponding to the employment category can be determined as 6 hours. It can also be determined that the starting time for the recruitment category is 13: 00, end time 19: 00, and so on.
In addition, the groups can be sorted according to the sequence of the average labor number prediction result from low to high; and then, respectively determining the corresponding required issued recruitment number information in each recruitment category according to the sequence from low to high.
Specifically, for the employment category of the lowest layer, the maximum value of the employment demand prediction result corresponding to the unit time period in the corresponding group is used as the required issued employment number corresponding to the employment category; and for the recruitment category of the high layer, according to the difference between the maximum value of the recruitment demand prediction result corresponding to the unit time period in the corresponding group and the determined recruitment quantity in the recruitment category of the low layer, the recruitment quantity required to be issued corresponding to the recruitment category is used. For example, the four groups are a first group, a second group, a third group, and a fourth group, which are sorted from low to high according to the average value of the number-of-workers prediction results. The determination of the amount of labor required may be made first for the first set of corresponding labor categories. Specifically, the maximum value of the prediction results of the number of uses for each unit time period in the group can be extracted, and is, for example, 19: 00-20: and 00, corresponding to 22 persons in the unit time period, the number of required releases of the first category can be determined as 22 persons. In this case, the number of persons who are delivered may be larger than the number of persons required for prediction for other unit time periods in the group, and a part of the labor may be redundant.
When determining the required amount of labor for the second group of corresponding labor categories, the maximum value of the predicted amount of labor for each unit time period in the group may be extracted, for example, 15: 00-16: 00 corresponds to 45 persons per unit time period. At this time, since the duration of continuous labor of the first class also covers the period of continuous labor corresponding to the second group, when determining the number of workers corresponding to the second class of workers, the determined number of workers to be released in the first layer may be first subtracted, and then the number of workers to be released in the second layer may be determined, for example, specifically 45 to 22 to 23 people, and so on.
In a word, according to the fourth embodiment, the continuous labor duration of the specific required labor category, the start-stop time corresponding to each category, the labor amount and other information can be determined in an automatic manner, so that occupation of human resources required in the specific manual configuration process can be avoided, and meanwhile, the efficiency can be improved.
EXAMPLE five
With regard to the various solutions provided in the foregoing embodiments for determining and releasing the employment requirement, there may be various practical application scenarios, for example, in the fifth embodiment, one of the application scenarios is provided, and specifically, the prediction may be performed on the employment requirement of a specific worker in a specific entity store and the determination of a specific employment category. Specifically, the fifth embodiment provides a method for processing labor demand information, and the method specifically may include:
acquiring recruitment demand prediction information of an operator in a target entity shop within a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the prediction result information of the required recruitment number corresponding to each unit time period;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; the recruitment duration corresponding to the same continuous recruitment category comprises a plurality of continuous unit time periods.
In particular, the operator may have some differences in specific working abilities and proficiency among different individuals in specific implementations. Therefore, when the specific recruitment requirement is issued, the requirements for information such as specific worker capability can be determined according to the information such as the characteristics of the specific corresponding recruitment time interval, and the information is issued together, so that specific suppliers and the like can provide workers more meeting the recruitment requirements in each time interval. In the case of combining the above information such as the capability of the specific worker, when the specific number of workers is predicted, the specific number of workers may be determined by combining the specific information of the capability of the specific worker, for example, in a certain unit time period, if the specific worker is a worker with ordinary capability, 50 persons are generally required, but if the specific worker with relatively strong capability is used, only 40 persons are required, and the like.
EXAMPLE six
The sixth embodiment mainly provides another application scenario of the employment requirement, that is, the employment requirement for the robot in places such as a specific entity shop. For example, in a certain physical store, some services need to be provided by a robot, including a robot meal delivery service in a restaurant, or a cleaning service, or food prepared in a certain restaurant in a certain mall is delivered to a unified meal taking place in the mall, and waits for a deliverer to take a meal, and so on. In the above scenario, for some physical stores with chain properties, a certain number of robots may be configured for each physical store to meet basic daily requirements. More robots may be managed by headquarters and the like in a unified manner, and on a short day of activity, stores may be configured according to actual needs of each physical store. Alternatively, for different physical stores in the same mall or even on the same floor, the specific robot may be managed by the mall in a unified manner, and when a certain physical store needs to provide a service using the robot, the request needs to be applied to or sent to the physical store such as the mall. The shopping mall can provide a corresponding number of robots for the restaurant according to specific requirements, and the entity shops in the shopping mall can obtain the services provided by the robots in a mode of renting the shopping mall. In short, under various different scenes, the number of workers for a specific robot in a specific target time period can be predicted in advance, in order to improve efficiency and avoid too frequent worker changes, the worker classification can be performed in the manner in the embodiment, and the duration of continuous work of the robot under various worker categories, and the information such as specific corresponding starting time, ending time, the number of workers and the like can be determined. Then, an entity such as a specific headquarters or a mall may perform a specific robot dispatch for a specific entity shop based on the labor demand information. Specifically, the sixth embodiment provides a method for processing labor requirement information of a robot, including:
acquiring recruitment requirement prediction information of the robot in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the required recruitment quantity prediction result information corresponding to the unit time periods respectively;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; the recruitment duration corresponding to the same continuous recruitment category comprises a plurality of continuous unit time periods.
Specifically, the labor demand prediction information of the robot in the target restaurant within the target time period may be obtained, where the robot is configured to provide a service of delivering food (to a specific dining table), cleaning and/or transporting food processed and manufactured in the target restaurant to a specified place (to a unified goods pick-up place in a shopping mall, etc.) in the target restaurant.
EXAMPLE seven
The seventh embodiment provides another specific application scenario, that is, some scenarios that require the use of a vehicle to provide services. The specific vehicle may be a network reservation vehicle (referred to as a network reservation vehicle for short), or an unmanned transport vehicle used for tallying goods in a large warehouse or the like or transporting goods between different areas, or the like. In the scene of the network appointment, the vehicle employment demand can be predicted in a specific geographical area or the like. For example, for a certain city, the labor demand of each administrative division for network appointment in a certain target time period in the future can be predicted. Then, the method in the foregoing embodiment is used to classify the specific employment requirements, and determine the continuous employment duration, the start-stop time, the employment number, and the like of each employment category. After the specific demand is issued, the specific vehicle can be scheduled in advance by a specific network car reservation scheduling party, so that the number of vehicles which can provide service in the corresponding time period in each administrative district can meet the actual demand.
In some large-scale warehouses, the warehouse may be divided into a plurality of floors due to a large area, and the like, and therefore, in order to improve efficiency of operations such as stocking goods, picking goods, transferring goods in the warehouse, and the like, and reduce occupation of manpower resources, some warehouses may also use unmanned vehicles for operations. Similar to physical stores, some warehouses may also have a unified manager, and some temporarily generated demands for a large amount of labor for unmanned vehicles may need to be forecasted in advance and issued to the manager. In this case, the scheme provided in the embodiment of the present application can also be used for implementation. Specifically, the seventh embodiment further provides a vehicle demand information processing method, including:
acquiring recruitment demand prediction information of a vehicle in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the required recruitment number prediction results corresponding to the unit time periods;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; the recruitment duration corresponding to the same continuous recruitment category comprises a plurality of continuous unit time periods.
Corresponding to the first embodiment, an embodiment of the present application further provides an employment requirement information processing apparatus, and referring to fig. 7, the apparatus may specifically include:
a prediction information obtaining unit 701, configured to obtain the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
a configuration interface providing unit 702, configured to provide an employment requirement configuration interface, and provide a first visualization chart corresponding to the prediction information and a plurality of optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations, and the continuous employment durations comprise a plurality of continuous unit time periods;
the visualized operation object combining unit 703 is configured to add a corresponding visualized operation object to the histogram according to the selected employment hierarchy, so that the similarity between the combined second visualized chart and the first visualized chart meets a preset condition by combining the visualized operation objects corresponding to the multiple different employment hierarchies.
The prediction information obtaining unit may be specifically configured to: predicting the total amount of the needed human resources according to the information of the number of the orders needing to be processed in the target time period in the target entity shop; and acquiring the recruitment requirement prediction information in the target time period according to the amount information of available human resources in the target time period paved by the target entity store and the total amount of the required human resources.
In a specific implementation, the apparatus may further include:
an operation information receiving unit, configured to receive operation result information performed on the visualized operation object;
and the information determining unit is used for determining the start-stop time information and the recruitment quantity information of the corresponding recruitment hierarchy according to the operation result.
Specifically, the operation information receiving unit may be specifically configured to receive a horizontal dragging operation performed on the visualization operation option, so as to determine start-stop time information corresponding to the labor hierarchy.
Alternatively, the operation information receiving unit may be configured to:
and receiving longitudinal scaling operation executed on the visualization operation option to determine the recruitment quantity information corresponding to the recruitment hierarchy.
Wherein, the configuration interface further comprises a data table, and the device further comprises:
and the data adding unit is used for adding the start-stop time information and the recruitment quantity information of the corresponding recruitment hierarchy into the data table according to the operation result of the visual operation object.
Wherein the visual operation object is semitransparent.
The width of the visual operation object corresponds to the labor hour of the labor layer and is fixed.
The visual operation object corresponding to the longest labor duration is preferentially added into the histogram, and the visual operation object added later can be placed on the left side, the right side or the upper side of the visual operation object added earlier, and no gap exists between the visual operation object and the histogram.
The number of visual operation objects corresponding to the same employment hierarchy is limited.
In addition, the apparatus may further include:
the operation option providing unit is used for providing operation options for issuing the labor demand;
and the issuing unit is used for issuing the recruitment requirement information obtained by combining the visual operation objects after receiving the operation instruction through the operation option.
Corresponding to the second embodiment, an embodiment of the present application further provides an employment requirement information processing apparatus, and referring to fig. 8, the apparatus may specifically include:
the release request receiving unit 801 is configured to receive recruitment requirement release request information submitted by a client, where the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and a similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and the employment requirement issuing unit 802 is configured to issue the employment requirement.
Corresponding to the three phases of the embodiment, the embodiment of the present application further provides an employment requirement information processing apparatus, referring to fig. 9, the apparatus may specifically include:
the recruitment requirement receiving unit 901 is configured to receive recruitment requirement information, where the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and a similarity between a combined second visual chart and a first visual icon corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
an operation option providing unit 902, configured to provide an operation option for picking up a task corresponding to the employment requirement, so as to pick up the task by using the employment hierarchy as a unit.
Corresponding to the fourth embodiment, the embodiment of the present application further provides an employment requirement information processing apparatus, referring to fig. 10, where the apparatus may specifically include:
a prediction information obtaining unit 1001 configured to obtain employment demand prediction information in a target time period, where the target time period includes a plurality of unit time periods, and the prediction information includes required employment quantity prediction result information corresponding to each of the plurality of unit time periods;
the demand layering processing unit 1002 is configured to classify the employment demands according to distribution conditions of the employment quantity information corresponding to each unit time period in the employment demand prediction information, so as to determine continuous employment duration information corresponding to at least one employment category, and start-stop time and employment quantity information of each employment category; the recruitment duration corresponding to the same continuous recruitment category comprises a plurality of continuous unit time periods.
The demand stratification processing unit may specifically include:
the comparison subunit is used for comparing the employment quantity prediction results pairwise for a plurality of continuous unit time periods with the employment quantity prediction results larger than a preset threshold value;
a group generation subunit, configured to divide the unit time period into a plurality of groups according to the pairwise comparison result;
and the layering subunit is used for classifying the recruitment requirements according to the unit time periods in the groups and the corresponding recruitment quantity prediction results.
The hierarchical sub-unit may specifically include:
the time information determining subunit is used for determining the continuous recruitment duration of the corresponding recruitment hierarchy and the starting and stopping time point according to the maximum time span between unit time periods in the same group;
the sorting subunit is used for sorting the groups according to the sequence from low to high of the average employment number prediction result;
and the number of people determining subunit is used for respectively determining the corresponding required issued recruitment number information in each recruitment category according to the sequence from low to high.
Wherein the person number determination subunit may be specifically configured to:
for the recruitment hierarchy at the lowest layer, according to the maximum value of the recruitment requirement prediction result corresponding to the unit time period in the corresponding group, the recruitment number required to be issued corresponding to the recruitment class is taken as;
and regarding the recruitment hierarchy of the high layer, taking the difference value between the maximum value of the recruitment demand prediction result corresponding to the unit time period in the corresponding group and the determined recruitment quantity in the recruitment class of the low layer as the recruitment quantity required to be issued corresponding to the recruitment class.
In addition, an embodiment of the present application further provides an electronic device, including:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
acquiring the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations, and the continuous employment durations comprise a plurality of continuous unit time periods;
and adding corresponding visual operation objects in the histogram according to the selected recruitment hierarchy, so that the similarity between the combined second visual chart and the first visual chart meets a preset condition by combining the visual operation objects corresponding to a plurality of different recruitment hierarchies.
An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
receiving recruitment requirement issuing request information submitted by a client, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and the similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and issuing the employment demand.
And another electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
receiving recruitment requirement information, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment layering information, and the similarity between the combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and providing operation options for picking up the tasks corresponding to the employment demands so as to pick up the tasks by taking the employment hierarchies as units.
And another electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
acquiring recruitment requirement prediction information in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the number of recruitment required prediction results corresponding to the unit time periods;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; the recruitment duration corresponding to the same continuous recruitment category comprises a plurality of continuous unit time periods.
FIG. 11 illustrates an architecture of an electronic device, which may include, in particular, a processor 1110, a video display adapter 1111, a disk drive 1112, an input/output interface 1113, a network interface 1114, and a memory 1120. The processor 1110, the video display adapter 1111, the disk drive 1112, the input/output interface 1113, the network interface 1114, and the memory 1120 may be communicatively connected by a communication bus 1130.
The processor 1110 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solution provided by the present Application.
The Memory 1120 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random access Memory), a static storage device, a dynamic storage device, or the like. The memory 1120 may store an operating system 1121 for controlling the operation of the electronic device 1100, a Basic Input Output System (BIOS) for controlling low-level operations of the electronic device 1100. In addition, a web browser 1123, a data storage management system 1124, and a labor demand information processing system 1125, etc. may also be stored. The labor demand information processing system 1125 may be an application program for implementing the operations of the foregoing steps in this embodiment. In summary, when the technical solution provided by the present application is implemented by software or firmware, the relevant program codes are stored in the memory 1120 and called for execution by the processor 1110.
The input/output interface 1113 is used for connecting an input/output module to realize information input and output. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
Network interface 1114 is used to connect to a communications module (not shown) to enable the device to interact with other devices for communication. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
In addition, the electronic device 1100 may also obtain information of specific pickup conditions from the virtual resource object pickup condition information database 1141 for performing condition judgment, and the like.
It should be noted that although the above devices only show the processor 1110, the video display adapter 1111, the disk drive 1112, the input/output interface 1113, the network interface 1114, the memory 1120, the bus 1130 and so on, in a specific implementation, the devices may also include other components necessary for normal operation. Furthermore, it will be understood by those skilled in the art that the apparatus described above may also include only the components necessary to implement the solution of the present application, and not necessarily all of the components shown in the figures.
From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present application may be essentially or partially implemented in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments of the present application.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are only illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The method, the device and the electronic device for processing the labor demand information provided by the application are introduced in detail, specific examples are applied in the description to explain the principle and the implementation of the application, and the description of the embodiments is only used for helping to understand the method and the core idea of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, the specific embodiments and the application range may be changed. In view of the above, the description should not be taken as limiting the application.
Claims (33)
1. A labor demand information processing method is characterized by comprising the following steps:
acquiring the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations, and the continuous employment durations comprise a plurality of continuous unit time periods;
and adding a corresponding visual operation object in the first visual chart according to the selected recruitment hierarchy, so that the similarity between the combined second visual chart and the first visual chart meets a preset condition by combining the visual operation objects corresponding to a plurality of different recruitment hierarchies.
2. The method of claim 1,
the obtaining of the recruitment requirement prediction information in the target time period comprises:
predicting the total amount of the needed human resources according to the information of the number of the orders needing to be processed in the target time period in the target entity shop;
and acquiring the recruitment requirement prediction information in the target time period according to the amount information of available human resources in the target time period paved by the target entity store and the total amount of the required human resources.
3. The method of claim 1,
the first visual chart comprises a histogram, and the histogram comprises a first coordinate axis and a second coordinate axis, wherein the first coordinate axis corresponds to time information, and the second coordinate axis corresponds to people number information;
the visual operation object is a rectangular block, and the rectangular block has a default width value in the direction of a first coordinate axis and a default height value in the direction of a second coordinate axis; the width value is continuous recruitment duration information corresponding to the recruitment hierarchy, the height value corresponds to the recruitment number corresponding to the recruitment hierarchy, and the position of the visual operation object in the direction of the first coordinate axis corresponds to the start-stop time of recruitment.
4. The method of claim 3,
the width value of the rectangular block is a fixed value, and the height value and the position in the direction of the first coordinate axis are adjustable.
5. The method of claim 4, further comprising:
and receiving a dragging operation in the direction of the first coordinate axis, which is performed on the visualization operation option, so as to determine start-stop time information corresponding to the application layer.
6. The method of claim 4, further comprising:
and receiving telescopic operation performed on the visual operation option in the second coordinate axis direction so as to determine the recruitment quantity information corresponding to the recruitment hierarchy.
7. The method of claim 4,
and the visual operation object corresponding to the longest labor duration is preferentially added to the upper layer of the first visual chart, and the visual operation object added later is placed on the left side, the right side or the upper side of the visual operation object added earlier and has no gap with each other.
8. The method of claim 4,
the configuration interface further comprises a data table, and the method further comprises the following steps:
and adding the start-stop time information and the recruitment quantity information of the corresponding recruitment hierarchy into the data table according to the operation result of the visual operation object.
9. The method according to any one of claims 1 to 8,
the visual operation object is semitransparent.
10. The method according to any one of claims 1 to 8,
the number of visual operation objects corresponding to the same employment hierarchy is limited.
11. The method of any one of claims 1 to 8, further comprising:
providing an operation option for releasing the employment requirement;
and after receiving an operation instruction through the operation option, submitting the recruitment requirement information obtained by combining the visual operation objects to a server for issuing.
12. A labor demand information processing method is characterized by comprising the following steps:
receiving recruitment requirement issuing request information submitted by a client, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and the similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and issuing the employment demand.
13. A labor demand information processing method is characterized by comprising the following steps:
receiving recruitment requirement information, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment layering information, and the similarity between the combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and providing operation options for picking up the tasks corresponding to the employment demands so as to pick up the tasks by taking the employment hierarchies as units.
14. A labor demand information processing method is characterized by comprising the following steps:
acquiring recruitment requirement prediction information in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the number of recruitment required prediction results corresponding to the unit time periods;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; the recruitment duration corresponding to the same continuous recruitment category comprises a plurality of continuous unit time periods.
15. The method of claim 14,
the classifying of the employment requirement comprises the following steps:
comparing every two of the recruitment number prediction results in a plurality of continuous unit time periods with recruitment number prediction results larger than a preset threshold value;
dividing the unit time period into a plurality of groups according to the pairwise comparison result;
and classifying the recruitment requirements according to the unit time period in each group and the corresponding recruitment quantity prediction result.
16. The method of claim 15,
the classifying of the recruitment requirements according to the unit time period in each group and the corresponding recruitment quantity prediction result comprises the following steps:
determining continuous recruitment time length and starting and stopping time points corresponding to the recruitment categories according to the maximum time span among unit time periods in the same group;
sorting the groups according to the sequence of the average labor number prediction result from low to high;
and respectively determining the corresponding required issued recruitment quantity information in each recruitment class according to the sequence from low to high.
17. The method of claim 16,
the step of respectively determining the corresponding required issued recruitment quantity information in each recruitment category according to the sequence from low to high comprises the following steps:
for the recruitment category of the lowest layer, according to the maximum value of the recruitment requirement prediction result corresponding to the unit time period in the corresponding group, the recruitment quantity required to be issued corresponding to the recruitment category is taken as;
and regarding the recruitment category of the high layer, taking the difference value between the maximum value of the recruitment demand prediction result corresponding to the unit time period in the corresponding group and the determined recruitment quantity in the recruitment category of the low layer as the recruitment quantity required to be issued corresponding to the recruitment category.
18. The method of any one of claims 14 to 17, further comprising:
and generating and issuing the recruitment requirement information according to the processing result of the recruitment requirement classification.
19. A labor demand information processing method is characterized by comprising the following steps:
acquiring recruitment demand prediction information of an operator in a target entity shop within a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the prediction result information of the required recruitment number corresponding to each unit time period;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; and the continuous recruitment time length corresponding to the same recruitment type comprises a plurality of continuous unit time periods.
20. A method for processing labor demand information of a robot is characterized by comprising the following steps:
acquiring recruitment requirement prediction information of the robot in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the required recruitment quantity prediction result information corresponding to the unit time periods respectively;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; and the continuous recruitment time length corresponding to the same recruitment type comprises a plurality of continuous unit time periods.
21. The method of claim 20,
the obtaining of the work demand prediction information for the robot in the target time period includes:
the method comprises the steps of obtaining work demand prediction information of a robot in a target restaurant in a target time period, wherein the robot is used for providing service of delivering food, cleaning and/or conveying food processed and manufactured in the target restaurant to a designated place in the target restaurant.
22. A vehicle demand information processing method characterized by comprising:
acquiring recruitment demand prediction information of a vehicle in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the required recruitment number prediction results corresponding to the unit time periods;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; and the continuous recruitment time length corresponding to the same recruitment type comprises a plurality of continuous unit time periods.
23. The method of claim 22,
the obtaining of the information of the forecast of the work demand on the vehicle in the target time period includes:
and acquiring the recruitment demand prediction information of the network reserved rental vehicle within the target geographic area within the target time period.
24. The method of claim 22,
the obtaining of the information of the forecast of the work demand on the vehicle in the target time period includes:
and acquiring the information of the work demand prediction of the unmanned transport vehicle in the target time period of the target site.
25. The method of claim 24,
the target site comprises a target warehouse, and the unmanned transport vehicle is used for providing goods shelving, picking or in-warehouse conveying service for the target warehouse.
26. An employment requirement information processing apparatus characterized by comprising:
the prediction information obtaining unit is used for obtaining the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
the configuration interface providing unit is used for providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations; the continuous labor duration comprises a plurality of continuous unit time periods;
and the visual operation object combination unit is used for adding corresponding visual operation objects in the histogram according to the selected recruitment hierarchy so as to combine the visual operation objects corresponding to a plurality of different recruitment hierarchies to ensure that the similarity of the combined second visual chart and the first visual chart meets a preset condition.
27. An employment requirement information processing apparatus characterized by comprising:
the system comprises a release request receiving unit, a processing unit and a processing unit, wherein the release request receiving unit is used for receiving recruitment requirement release request information submitted by a client, the recruitment requirement information is obtained by combining visual operation objects corresponding to various optional recruitment hierarchical information, and the similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and the recruitment requirement issuing unit is used for issuing the recruitment requirement.
28. An employment requirement information processing apparatus characterized by comprising:
the recruitment requirement receiving unit is used for receiving recruitment requirement information, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and the similarity between the combined second visual chart and a first visual icon corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and the operation option providing unit is used for providing operation options for picking up the tasks corresponding to the employment requirements so as to pick up the tasks by taking the employment hierarchy as a unit.
29. An employment requirement information processing apparatus characterized by comprising:
the system comprises a prediction information obtaining unit, a prediction information obtaining unit and a processing unit, wherein the prediction information obtaining unit is used for obtaining recruitment requirement prediction information in a target time period, the target time period comprises a plurality of unit time periods, and the prediction information comprises required recruitment quantity prediction result information corresponding to the unit time periods respectively;
the demand layering processing unit is used for classifying the employment demands according to the distribution condition of the employment quantity information corresponding to each unit time period in the employment demand prediction information so as to determine continuous employment duration information corresponding to at least one employment category and start-stop time and employment quantity information of each employment category; and the continuous recruitment time length corresponding to the same recruitment type comprises a plurality of continuous unit time periods.
30. An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
acquiring the recruitment requirement prediction information in the target time period; the target time period comprises a plurality of unit time periods, and the prediction information comprises the required labor amount information corresponding to the unit time periods;
providing an employment requirement configuration interface, and providing a first visual chart corresponding to the prediction information and various optional employment layering information in the configuration interface; the multiple optional employment layers respectively correspond to different continuous employment durations, and the continuous employment durations comprise a plurality of continuous unit time periods;
and adding corresponding visual operation objects in the histogram according to the selected recruitment hierarchy, so that the similarity between the combined second visual chart and the first visual chart meets a preset condition by combining the visual operation objects corresponding to a plurality of different recruitment hierarchies.
31. An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
receiving recruitment requirement issuing request information submitted by a client, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment hierarchical information, and the similarity between a combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and issuing the employment demand.
32. An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
receiving recruitment requirement information, wherein the recruitment requirement information is obtained by combining visual operation objects corresponding to multiple optional recruitment layering information, and the similarity between the combined second visual chart and a first visual chart corresponding to pre-obtained recruitment requirement prediction information meets a preset condition;
and providing operation options for picking up the tasks corresponding to the employment demands so as to pick up the tasks by taking the employment hierarchies as units.
33. An electronic device, comprising:
one or more processors; and
a memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
acquiring recruitment requirement prediction information in a target time period, wherein the target time period comprises a plurality of unit time periods, and the prediction information comprises the information of the number of recruitment required prediction results corresponding to the unit time periods;
according to the distribution condition of the recruitment number information corresponding to each unit time period in the recruitment requirement prediction information, carrying out recruitment requirement classification to determine continuous recruitment duration information corresponding to at least one recruitment category, and the start-stop time and the recruitment number information of each recruitment category; and the continuous recruitment time length corresponding to the same recruitment hierarchy comprises a plurality of continuous unit time periods.
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