CN115860393A - Wisdom garden business recruitment management system - Google Patents
Wisdom garden business recruitment management system Download PDFInfo
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- CN115860393A CN115860393A CN202211566629.3A CN202211566629A CN115860393A CN 115860393 A CN115860393 A CN 115860393A CN 202211566629 A CN202211566629 A CN 202211566629A CN 115860393 A CN115860393 A CN 115860393A
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Abstract
The invention discloses an intelligent park recruitment management system, which belongs to the technical field of financial management and comprises a park resource module and a recommendation module; the park resource module is used for carrying out park recruitment resource management and obtaining a target enterprise field list of recruitment; the recommendation module is used for recommending the business inviting enterprises, acquiring enterprise details in the park, screening the enterprise details according to the business inviting target enterprise field list, acquiring a plurality of to-be-selected enterprises, and calculating the park division of each to-be-selected enterprise; evaluating the regional division of the city where the park is located on each enterprise to be selected, determining corresponding recommended enterprises according to the obtained park division and the regional division, generating the advantage data of the park on each recommended enterprise, and sending the obtained recommended enterprises and the corresponding advantage data to corresponding park managers; through resource management maximization, the advantages of the park are analyzed, park managers are assisted to reduce the business recruitment field, and the corresponding business recruitment success rate is improved.
Description
Technical Field
The invention belongs to the technical field of financial management, and particularly relates to an intelligent park business recruitment management system.
Background
The existing park management is mainly based on a mode of manually matching office software of a single edition to record the whole process information of an advertiser, and in the process, firstly, a large number of fixed assets of an operation unit need to be rented out, but the most suitable resident enterprise cannot be quickly and efficiently found out; resulting in difficulties in inviting businesses and failure to maximize the utilization of assets.
For example, patent with publication number CN113655924a discloses a method and system for intelligent management and recruitment display based on a digital park, the system includes: logging in a display interface and a main display interface; skipping to a main display interface after the login of the login display interface is successful, wherein the main display interface comprises: the menu display area comprises a data center module, a work management module, a display management module, a client management module and a policy management module which are sequentially arranged from top to bottom, and the top display area comprises a personal center module and an opinion feedback module; and the content main display area is used for displaying the content which is bound with each module in advance.
The intelligent park recruitment management system is used for improving the management efficiency in a park by intensively displaying various information such as enterprise development related policies, enterprise information, park visitors and the like in the park, but the mode is applied in various fields, the played effect is not obvious, and the effect on the recruitment of the park is small.
Disclosure of Invention
In order to solve the problems of the scheme, the invention provides an intelligent park enrollment management system.
The purpose of the invention can be realized by the following technical scheme:
an intelligent park business recruitment management system comprises a park resource module and a recommendation module;
the park resource module is used for carrying out park business recruitment resource management and obtaining a business recruitment target enterprise field list;
the recommendation module is used for recommending business inviting enterprises, acquiring enterprise details in a park, screening the enterprise details according to a business inviting target enterprise field list, acquiring a plurality of to-be-selected enterprises, and calculating park division of each to-be-selected enterprise; and evaluating the regional scores of the cities in which the parks are located for the enterprises to be selected, determining corresponding recommended enterprises according to the obtained park scores and the regional scores, generating the advantage data of the parks for the recommended enterprises, and sending the obtained recommended enterprises and the corresponding advantage data to corresponding park managers.
Further, the working method of the garden resource module comprises the following steps:
identifying park resources in a park, acquiring a recruiter evaluation item table, classifying the park resources based on the recruiter evaluation item table to acquire corresponding evaluation item data, analyzing the acquired evaluation item data to acquire a corresponding evaluation item, matching a weighted value of the corresponding evaluation item from the recruiter evaluation item table, and setting a recruiter target enterprise field list according to the acquired evaluation item evaluation value and the corresponding weighted value.
Further, the method for setting the listing of the business target areas of the recruiter according to the obtained evaluation value of the evaluation item and the corresponding weight value comprises the following steps:
labeling the evaluation item evaluation value as PGi, where i represents the corresponding evaluation item, i =1, 2, … …, n being a positive integer; marking the obtained weight value as QZi according to a formula
And calculating coordinate values corresponding to the evaluation items, integrating the obtained coordinate values into characteristic coordinates, and matching the corresponding business target enterprise field list according to the obtained characteristic coordinates.
Further, the method for calculating the division of the enterprise gardens to be selected comprises the following steps:
setting the weight coefficient of each evaluation item according to the data of the enterprise to be selected, and marking the obtained weight coefficient as beta i, wherein i represents the evaluation item; obtaining coordinate value ZBi corresponding to each evaluation item according to formula
Compute corresponding park partitions。
Further, the method for determining the corresponding recommended enterprises according to the obtained garden distinction and regional distinction comprises the following steps:
and marking the obtained areas as QZ, calculating corresponding recommended values according to a formula TZP = b1 XYQ + b2 XQZ, and marking the enterprises to be selected with the recommended values TZP larger than a threshold value X1 as recommended enterprises.
The system further comprises a recruitment tracking module, wherein the recruitment tracking module is used for displaying a recruitment result in real time, acquiring a list of recommended enterprises, acquiring the recruitment progress of each recommended enterprise in real time, establishing a corresponding display model based on the obtained recruitment progress of each recommended enterprise, and displaying the corresponding recruitment progress in real time through the established display model.
Further, when the display model has the corresponding recruiting result, the recruiting result comprises the success of the recruiting, the failure of the recruiting and the termination progress corresponding to the failure of the recruiting, the corresponding recommendation result data is integrated according to the obtained recruiting result, and the recommendation result data is stored.
The service module is used for performing parking service on the recommended enterprise after the recruitment is successful, acquiring information of the parked enterprise, analyzing parking requirements of the enterprise according to the acquired information of the parked enterprise, and sending the acquired parking requirements of the enterprise to corresponding managers.
Compared with the prior art, the invention has the beneficial effects that:
the intelligent business recruitment and enterprise residence management in the park is realized through the mutual cooperation of the park resource module, the recommendation module, the business recruitment tracking module and the service module; the park resource module is used for integrating and managing various resources, so that enterprises which are suitable for being matched can be conveniently and accurately recruited, the advantages of the park are analyzed through resource management maximization, the park can clearly know the attraction degree of the park to the enterprises in different fields, the park managers are assisted to reduce the recruitment field, and the corresponding success rate of recruiting merchants is improved; through the setting of service module, be convenient for integrate the service ability in garden, for the business of entrying provides the service item of thoughtful interest, help entrying more efficient business of entrying the enterprise and entrying the garden to for the recruitment of garden provides the competitiveness.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an intelligent campus recruitment management system includes a campus resource module, a recommendation module, a recruitment tracking module, and a service module;
the park resource module, the recommendation module, the recruiting and tracking module and the service module are in communication connection.
The park resource module is used for carrying out park recruitment resource management, such as service resources of various enterprises served in the park, human resources of a city, potential consumer resources and the like, and is used for carrying out integration management on various resources, so that the park resource module is convenient for accurately matching proper enterprises to recruit the park, analyzes the advantages of the park through the maximization of resource management and improves the success rate of corresponding recruitment; the specific method comprises the following steps:
identifying park resources in a park, wherein the park resources comprise data which are beneficial to recruiting and comprise parked enterprise information, equipment auxiliary data, parking management data, park environment data and the like, and acquiring a recruiter evaluation item table, wherein the recruiter evaluation item table is set manually, evaluation items are items which have influence on the recruiter, such as park environment, recruitment environment, potential consumer condition, service data and other corresponding evaluation items, each evaluation item is provided with a corresponding weight value, and the evaluation items are mainly set according to the focus of attention of the corresponding enterprise in historical recruiter data; the method comprises the steps of classifying park resources based on a recruiter evaluation item table to obtain corresponding evaluation item data, analyzing the obtained evaluation item data to obtain corresponding evaluation item evaluation values, matching weight values of corresponding evaluation items from the recruiter evaluation item table, and setting a recruiter target enterprise field list according to the obtained evaluation item evaluation values and the corresponding weight values.
And classifying the park resources based on the recruiter evaluation item table, identifying data belonging to evaluation items in the recruiter evaluation item table in the park resources, and performing corresponding classification, namely that the evaluation items do not necessarily correspond to corresponding data in the park resources.
Through carrying out garden resource management, the clear understanding of help garden is to the attraction degree of different field enterprises in this garden, and supplementary garden managers dwindles the field of inviting the merchant, improves efficiency of inviting the merchant and success rate.
The method for analyzing the obtained evaluation item data comprises the following steps: the evaluation method comprises the steps of setting a scoring rule corresponding to each evaluation item in a manual mode, evaluating based on an existing evaluation method, or establishing a corresponding evaluation model based on an existing CNN network or DNN network, setting a corresponding training set in a manual mode for training, and carrying out intelligent evaluation through the evaluation model after the training is successful.
The method for setting the listing of the business target enterprise fields according to the obtained evaluation value of the evaluation item and the corresponding weight value comprises the following steps:
labeling the evaluation item evaluation value as PGi, where i represents the corresponding evaluation item, i =1, 2, … …, n being a positive integer; marking the obtained weight value as QZi according to a formula
Calculating coordinate values corresponding to the evaluation items, integrating the obtained coordinate values into characteristic coordinates, and calculating the coordinate values according to the characteristic coordinatesThe obtained feature coordinates match a corresponding listing of business target enterprise domains.
And integrating the obtained coordinate values into a characteristic coordinate, namely integrating according to the sequence corresponding to each evaluation item, wherein if the coordinate values corresponding to each check item are 1,2,3 and 4, the characteristic coordinate is (1,2,3,4).
The method for matching the corresponding business recruitment target enterprise domain list according to the obtained characteristic coordinates comprises the following steps:
a plurality of groups of simulation coordinates are set according to the existing large amount of park data simulation, the acquisition mode of the simulation coordinates is the same as that of characteristic coordinates, batch generation can be carried out, and the simulation coordinates are input into a coordinate space; arranging sequences of the enterprise fields under different conditions are set through a mode of discussion and analysis by an expert group to form a recruiting target enterprise field list, generally, only about 5 business fields are required to be ordered, because some enterprise fields can be listed as one type, the business fields are ordered according to the type, area ranges corresponding to the recruiting target enterprise field list are divided in a coordinate space according to the corresponding recruiting target enterprise field list, the operation is carried out by combining the existing clustering algorithm, namely, coordinate areas corresponding to a plurality of recruiting target enterprise field lists are formed in the final coordinate space, and the corresponding establishment can be carried out through a manual mode by specifically combining the description; and acquiring the characteristic coordinates to be matched, inputting the characteristic coordinates into a coordinate space, and matching the corresponding business recruitment target enterprise field list.
The recommendation module is used for recommending the business recruitment enterprises, and the specific method comprises the following steps:
acquiring enterprise details of a park, namely various enterprise resources acquired by the park, including enterprise position, tax, scale, business scope, field, establishment time, consumption oriented value and other data;
screening the enterprise details according to the business recruitment target enterprise field list to obtain a plurality of to-be-selected enterprises, and calculating the garden distinction of each to-be-selected enterprise; and evaluating the regional scores of the cities where the parks are located for the enterprises to be selected, determining corresponding recommended enterprises according to the obtained park scores and the regional scores, generating the advantage data of the parks for the recommended enterprises, and sending the obtained recommended enterprises and the corresponding advantage data to corresponding park managers.
The method for calculating the division of the enterprise gardens to be selected comprises the following steps:
setting the weight coefficient of each evaluation item according to the data of the enterprise to be selected, and marking the obtained weight coefficient as beta i, wherein i represents the evaluation item; obtaining the coordinate value ZBi corresponding to each evaluation item according to the formula
The corresponding garden distinction is calculated.
The method for determining the corresponding recommended enterprise according to the obtained garden distinction and regional distinction comprises the following steps:
marking the obtained areas as QZ, calculating corresponding recommended values according to a formula TZP = b1 XYQ + b2 XQZ, marking the to-be-selected enterprises with the recommended values TZP larger than a threshold value X1 as recommended enterprises, and setting the threshold value X1 through discussion by an expert group.
The method comprises the steps of setting weight coefficients of evaluation items according to enterprise data to be selected, setting standard weight coefficients of different evaluation items of the enterprise fields in a manual mode in the setting process of a business recruitment target enterprise field list, namely setting the standard weight coefficients of the different evaluation items of the enterprise fields in the manual mode, wherein the weight coefficients of the evaluation items corresponding to the different enterprise fields are different and are mainly set according to working properties of the enterprise fields, analyzing the enterprise data to be selected, correcting the standard weight coefficients to obtain corresponding weight coefficients, analyzing the enterprise data, judging whether the check items have obvious trends according to historical operating data of the enterprise data, further performing corresponding adjustment if the check items do not have the trends, specifically establishing corresponding weight analysis models based on a CNN network or a DNN network, setting corresponding training sets in the manual mode for training, analyzing the data through the successfully trained weight analysis models to obtain adjustment values of the evaluation items of the enterprise, and adjusting the corresponding standard weight coefficients through the obtained adjustment values.
The method comprises the steps that a city where a park is located is evaluated to the regional division of each enterprise to be selected, the regional division is a score which is attractive to the enterprise to be selected, such as regional data of relevant policies, tax deduction, sales, transportation, climate and the like, the attraction degree of the enterprise to be selected in the park is evaluated according to the regional data and the data of the enterprise to be selected, then the corresponding regional division is comprehensively evaluated, specifically, a corresponding regional analysis model can be established based on a CNN network or a DNN network, a corresponding training set is established in a manual mode for training, and the regional data and the data of the enterprise to be selected are analyzed through the successfully trained regional analysis model to obtain the corresponding regional division.
Generating the superiority data of the park to each recommended enterprise, namely identifying the direction of the recommended enterprise in the process of determining the recommended value, correspondingly marking the corresponding laterality data, so that subsequent workers can carry out park recommendation in a targeted manner, specifically marking the superiority data by using the prior art, or carrying out mark extraction in a manual mode according to the recommended value calculation process.
The business recruitment tracking module is used for displaying business recruitment results in real time, acquiring a recommendation enterprise list, acquiring business recruitment progress of each recommendation enterprise in real time and acquiring the business recruitment progress through corresponding business recruitment personnel; establishing a corresponding display model based on the obtained recruitment progress of each recommended enterprise, wherein the display model is used for displaying the recruitment progress and the recruitment result of the corresponding recommended enterprise in real time and can be established through the existing display technology as a data display model; and displaying the corresponding recruitment progress in real time through the established display model.
When the display model has a corresponding recruiter result, the recruiter result comprises a termination progress corresponding to the success of recruiting, the failure of recruiting and the failure of recruiting, and the termination progress is identified by the step in the recruiter progress; and integrating corresponding recommendation result data according to the obtained solicited quotient result, and storing the recommendation result data. For subsequent recommendation process optimization.
And integrating corresponding recommendation result data according to the obtained solicited business result, namely, sorting the corresponding recommendation enterprise data, recommendation value calculation process and recommendation result into recommendation result data, presetting corresponding sorting rules, sorting in various modes such as direct packaging, accurate data extraction and the like, and specifically sorting the data by using the existing sorting technology according to the requirements of the park.
The service module is used for carrying out the parking service on the recommended enterprises after successful business recruitment, acquiring the information of the parked enterprises, including enterprise types, work contents, the number of people, recommended advantage data and the like, analyzing the parking requirements of the enterprises according to the acquired parking enterprise information, and sending the acquired parking requirements of the enterprises to corresponding managers.
The method comprises the steps of analyzing the resident requirements of the enterprises according to the acquired resident enterprise information, namely judging parts which are possibly urgently needed to be assisted in the resident process according to the resident enterprise information, such as government affair services including local policies and registration flows, service assistance including equipment entering and leaving in the park process, service assistance including employee recruitment, house renting and the like, specifically counting corresponding service items according to the actual service capacity of the park, and then carrying out intelligent analysis by combining with the existing analysis technology, wherein if the resident service items of non-local enterprises are, a corresponding service item matching table can be established, and corresponding matching is carried out according to the enterprise information.
Through the setting of service module, be convenient for integrate the service ability in garden, for the business of entrying provides the service item of thoughtful interest, help entrying more efficient business of entrying the enterprise and entrying the garden to for the recruitment of garden provides the competitiveness.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the most approximate real condition, and the preset parameters and the preset threshold values in the formula are set by the technical personnel in the field according to the actual condition or obtained by simulating a large amount of data.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (8)
1. An intelligent park business recruitment management system is characterized by comprising a park resource module and a recommendation module;
the park resource module is used for carrying out park recruitment resource management and obtaining a target enterprise field list of recruitment;
the recommendation module is used for recommending business inviting enterprises, acquiring enterprise details in a park, screening the enterprise details according to a business inviting target enterprise field list, acquiring a plurality of to-be-selected enterprises, and calculating park division of each to-be-selected enterprise; and evaluating the regional scores of the cities where the parks are located for the enterprises to be selected, determining corresponding recommended enterprises according to the obtained park scores and the regional scores, generating the advantage data of the parks for the recommended enterprises, and sending the obtained recommended enterprises and the corresponding advantage data to corresponding park managers.
2. The intelligent campus recruitment management system of claim 1 wherein the campus resource modules operate by:
identifying park resources in a park, acquiring a recruiter evaluation item table, classifying the park resources based on the recruiter evaluation item table to acquire corresponding evaluation item data, analyzing the acquired evaluation item data to acquire a corresponding evaluation item, matching a weighted value of the corresponding evaluation item from the recruiter evaluation item table, and setting a recruiter target enterprise field list according to the acquired evaluation item evaluation value and the corresponding weighted value.
3. The intelligent campus recruitment management system of claim 1 wherein the method of setting the list of recruitment target business areas according to the evaluation values and the corresponding weight values comprises:
labeling the evaluation item evaluation value as PGi, where i represents the corresponding evaluation item, i =1, 2, … …, n being a positive integer; marking the obtained weight value as QZi according to a formula
And calculating coordinate values corresponding to the evaluation items, integrating the obtained coordinate values into characteristic coordinates, and matching the corresponding business target enterprise field list according to the obtained characteristic coordinates.
4. The intelligent park recruitment management system of claim 3 wherein the method of calculating each candidate park division comprises:
setting the weight coefficient of each evaluation item according to the data of the enterprise to be selected, and marking the obtained weight coefficient as beta i, wherein i represents the evaluation item; obtaining the coordinate value ZBi corresponding to each evaluation item according to the formula
The corresponding garden distinction is calculated.
5. The intelligent campus facilitator management system of claim 4, wherein the method for determining the recommended business based on the obtained campus and regional divisions comprises:
and marking the obtained areas as QZ, calculating corresponding recommended values according to a formula TZP = b1 multiplied by YQ + b2 multiplied by QZ, and marking the to-be-selected enterprises with the recommended values TZP larger than a threshold value X1 as recommended enterprises.
6. The intelligent campus recruitment management system of claim 1 further comprising a recruitment tracking module, wherein the recruitment tracking module is configured to display the recruitment result in real time, obtain the list of recommended enterprises, obtain the recruitment progress of each recommended enterprise in real time, establish a corresponding display model based on the obtained recruitment progress of each recommended enterprise, and display the corresponding recruitment progress in real time through the established display model.
7. The intelligent campus recruitment management system of claim 6 wherein the display model is configured to store the recommendation result data by integrating the recommendation result data corresponding to the recruitment results when the recruitment results include the termination progress corresponding to the recruitment success, the recruitment failure and the recruitment failure.
8. The intelligent park recruitment management system according to claim 1, further comprising a service module, wherein the service module is used for performing a resident service on the recommended enterprise after successful recruitment, acquiring resident enterprise information, analyzing an enterprise resident requirement according to the acquired resident enterprise information, and sending the acquired enterprise resident requirement to a corresponding manager.
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| CN202211566629.3A CN115860393A (en) | 2022-12-07 | 2022-12-07 | Wisdom garden business recruitment management system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116776392A (en) * | 2023-07-26 | 2023-09-19 | 园创品牌管理(北京)有限公司 | Double nine-dimensional management method and system for improving intelligent market number |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116776392A (en) * | 2023-07-26 | 2023-09-19 | 园创品牌管理(北京)有限公司 | Double nine-dimensional management method and system for improving intelligent market number |
| CN116776392B (en) * | 2023-07-26 | 2024-02-20 | 园创品牌管理(北京)有限公司 | Double nine-dimensional management method and system for improving intelligent market number |
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