CN118052528B - Human resource management system based on AI blue-collar intelligent service platform - Google Patents
Human resource management system based on AI blue-collar intelligent service platform Download PDFInfo
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Abstract
The invention relates to the technical field of human resource management, and discloses a human resource management system based on an AI blue-collar intelligent service platform, which comprises a talent management module, an enterprise management module, a resource matching module and a job-seeking interview module. This manpower resources management system based on AI blue neck intelligent service platform sets up talent resume unit through talent management module and gathers resume dataset, reduce the read-write input, nimble service blue neck workman crowd uses the sense to be good, label classification unit classification generates talent label data group Rcbq, enterprise management module gathers position dataset and classification generates demand label data group Xubq, unified label batchization classification mark blue neck and position, resource matching module is according to the label quantity by the multidirectional few resume of arranging and position, calculate and generate matching set Pejh, blue neck and enterprise both sides can set up different scoring standard, the automatic screening high-end object interview is communicated, manpower resources management matching efficiency is high.
Description
Technical Field
The invention relates to the technical field of human resource management of service platforms, in particular to a human resource management system based on an AI blue-collar intelligent service platform.
Background
The blue-collar is generally described as a worker engaged in physical or technical work, particularly a worker engaged in an industrial work such as manufacturing, construction, handcraft, and maintenance. The work content generally involves manual operations, mechanical operations, and work on a production line. Blue-collar professions are more related to physical labor than white-collar professions, rather than office work or knowledge work. With the development of technology and the rise of Artificial Intelligence (AI), the nature of blue-collar work is also changing. AI and automation are changing the traditional blue-collar working mode, creating new working opportunities while also eliminating old working skills. Some tasks with high repeatability and physical demands may be replaced by automation, while work requiring more skill and knowledge may occur. Meanwhile, the artificial intelligence technology is also needed to provide employment arrangement and living service for basic blue-collar workers, the AI technology is utilized to optimize the man-post matching process, the recruitment and job-seeking efficiency is improved, and an efficient, convenient and safe employment and human resource management environment is provided for blue-collar workers and enterprises.
At present, a traditional intelligent service platform human resource management system is more laborious in acquiring industry dynamic and enterprise job recruitment information aiming at a blue-collar worker group, job hunting experience is not humanized enough, and human post matching efficiency is low.
Disclosure of Invention
Aiming at the defects of the prior art, the human resource management system based on the AI blue-collar intelligent service platform has the advantages of good use sense of a flexible service blue-collar worker group, high human resource management matching efficiency and the like, and solves the problems that the blue-collar worker group of the traditional intelligent service platform human resource management system is relatively laborious in acquiring position information, and the experience sense is not enough, and the human resource management matching efficiency is low.
In order to achieve the above purpose, the present invention provides the following technical solutions: the human resource management system based on the AI blue-collar intelligent service platform comprises a talent management module, an enterprise management module, a resource matching module and a job-seeking interview module;
the talent management module comprises a talent resume unit and a label classification unit, wherein the talent resume unit collects resume data sets through a file transmission interface or an AI intelligent voice device, the resume data sets are transmitted to the label classification unit through a network after numbered, the label classification unit establishes a label data set through a network connection database and numbered, and the label classification unit combines the label data sets according to the resume data sets to generate talent label data sets in a classified manner The talent management module is connected with the resource matching module through a network;
The enterprise management module comprises a job issuing unit and a skill alignment unit, wherein the job issuing unit collects a job data set through a file transmission interface or an AI intelligent video device, and transmits the job data set to the skill alignment unit through a network after numbering, and the skill alignment unit generates a demand label data set according to the job data set, combines a label data set and classifies the demand label data set The enterprise management module is connected with the resource matching module through a network;
the resource matching module comprises a supply arrangement unit, a demand arrangement unit and a person post matching unit, wherein the supply arrangement unit is used for marking a data set according to talents Sequentially arranging resume data sets and transmitting the data to a post matching unit, wherein the requirement arranging unit is used for labeling data sets/>, according to requirementsSequentially arranging the job position data sets and transmitting the data to a post matching unit, wherein the post matching unit performs the post matching according to the talent label data set/>Demand label data setThe resume data set and the job data set are calculated to generate a matching set/>The resource matching module is connected with the job-seeking interview module through a network;
The job-seeking interview module is connected with the AI blue-collar intelligent service platform through a network, comprises a talent interview unit and an enterprise recruitment unit, and is provided with a key interview model through a user side The talent interview unit is based on a key interview model/>For matching set/>Grading, and returning to the user side through a network, waiting for the communication enterprise to perform interview after screening, wherein the enterprise manager sets a key recruitment model/>, through the enterprise sideThe enterprise recruitment unit performs/>, according to the key recruitment modelFor matching set/>Scoring is carried out, the scoring is transmitted back to the enterprise end through the network, and the blue lead is invited to carry out interview after waiting to be screened.
Preferably, the resume document is input through a connection file transmission interface or the resume content is input through online voice of a voice device to form a resume data set, the talent resume unit numbers the resume data set according to the resume data set characteristics, and the resume data set numbers are as follows、/>、/>、.../>。
Preferably, the tag data set is composed of a skill tag data set, a work age tag data set and a region tag data set, the tag classification unit numbers the skill tag data set, the work age tag data set and the region tag data set according to the feature of the tag data set, and the tag data set numbers are as follows、/>And/>。
Preferably, the tag classification unit combines the tag data sets according to the resume data sets to generate talent tag data sets in a classified mannerThe classification generation algorithm formula is as follows:
；
In the formula (i), Representing talent tag data group,/>Talent skill label data representing the classification of a resume dataset according to a skill label dataset,/>Talent age tag data representing classification of resume data sets based on age tag data setsAnd the talent regional tag data is generated by classifying the resume data set according to the regional tag data set.
Preferably, the enterprise manager inputs the job recruitment document through a connection file transmission interface or records the job recruitment content through an AI intelligent video device to form a job data set, the job issuing unit numbers the job data set according to the characteristic of the job data set, and the job data set is numbered as follows、/>、/>、.../>。
Preferably, the skill alignment unit generates the demand label data set according to the job position data set and the label data set in a classification wayThe classification generation algorithm formula is as follows:
；
In the formula (i), Representing demand label data set,/>Representing job skill tag data generated by classifying a job dataset according to a skill tag dataset,/>Representing job age tag data generated by classifying a job data set according to the job age tag data set,/>And the position regional label data are generated by classifying the position data set according to the regional label data set.
Preferably, the supply arrangement unit is arranged according to talent tag data groupSequentially arranging the resume data sets, wherein the resume data sets have a plurality of tags, the talent resume sequence is front, and the demand arrangement unit is used for labeling the data sets/>, according to demandsAnd sequentially arranging the job data sets, wherein the recruitment positions with a large number of labels in the job data sets are positioned at the front.
Preferably, the person post matching unit is used for matching the person post according to the person talent label data groupDemand label dataset/>The resume data set and the job data set are calculated to generate a matching set/>The calculation formula is as follows:
；
In the formula (i), Representing a matching set,/>Representing the union portion of a specified talent tag dataset and a resume dataset,/>Representing a union portion of the specified demand label dataset and the job dataset,Representing a blue-collar talent and business job data set that performs a person-post match based on the tag data set.
Preferably, the talent interview unit is based on a focused interview modelFor matching set/>Scoring the matched enterprise job data, talent tag data set/>And demand label dataset/>The matching similarity is high, and the labels are the same in number and correspond to enterprises with high scores.
Preferably, the enterprise recruitment unit is configured to select the key recruitment model based on the key recruitment modelFor matching set/>Scoring the matched blue-collar talent data, and marking the talent label data group/>And demand label dataset/>The matching similarity is high, and the same number of tags corresponds to high blue collar scores.
Compared with the prior art, the human resource management system based on the AI blue-collar intelligent service platform has the following beneficial effects:
1. According to the invention, the talent resume unit is arranged to collect the resume data set through the talent management module, so that the blue-neck crowd with lower education level can conveniently input in a whole course through the AI intelligent voice device, the read-write input is reduced to the greatest extent, and the label classification unit generates the talent label data set in a classified manner according to the resume data set and the label data set by combining the label data set The enterprise management module sets a position issuing unit to collect a position data set, and the skill contraband unit generates a demand label data set in a classified manner according to the position data set and the label data set by combining the label data setThe staff interview unit is arranged by the staff interview module, and the blue collar crowd sets the key interview model/>, through the user sideTalent interview unit based on the focused interview model/>For matching set/>The matched enterprise position data are scored, the matching similarity is high, the labels are the same in number and correspond to the enterprises in a plurality, the score is high, and the use sense of the blue-collar workers is good.
2. The invention sets the supply arrangement unit and the demand arrangement unit through the resource matching module, thereby the talent label data groupAnd demand label dataset/>The resume data set and the job data set are sequentially arranged, the talent resume with a large number of labels and the job of the enterprise are positioned in front, and the post matching unit is used for matching the talents according to the talent label data set/>Demand label data setThe resume data set and the job data set are calculated to generate a matching set/>The blue-collar talents and the enterprise positions are matched rapidly, the job hunting interview module sets an enterprise recruitment unit, and an enterprise manager sets a key recruitment model/>, through an enterprise terminalThe enterprise recruitment unit performs/>, according to the key recruitment modelFor matching set/>The matched blue-collar talent data are scored, the matching similarity is high, the same number of tags corresponds to the blue-collar data, the scoring is high, and the matching efficiency of human resource management is high.
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FIG. 1 is a schematic diagram of the system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a human resource management system based on an AI blue-collar intelligent service platform comprises a talent management module, an enterprise management module, a resource matching module and a job-seeking interview module;
The talent management module comprises a talent resume unit and a label classification unit, wherein the talent resume unit collects resume data sets through a file transmission interface or an AI intelligent voice device, a blue-neck crowd inputs resume documents through a connection file transmission interface or inputs resume contents through online voice of the voice device, the blue-neck crowd with low education level is convenient to input in a whole course through the AI intelligent voice device, the read-write input is reduced to the greatest extent, the use feeling is flexible and simple, the talent resume data sets are transmitted to the label classification unit through a network after being numbered, and the resume data sets are numbered as follows 、/>、/>、.../>The serial numbers correspond to all the resumes of the talent resume units stored in the blue-neck crowd, the tag classification unit establishes a tag data set through a network connection database, the serial numbers are carried out, and the serial numbers of the tag data set are/>、/>And/>The label data set consists of a skill label data set, a work age label data set and a region label data set, and the label classification unit combines the label data set according to the resume data set to generate a talent label data set in a classification mannerThe talent management module is connected with the resource matching module through the network, and the classification generation algorithm formula is as follows:
；
In the formula (i), Representing talent tag data group,/>Talent skill label data representing the classification of a resume dataset according to a skill label dataset,/>Talent age tag data representing classification of resume data sets based on age tag data setsTalent regional tag data generated by classifying resume data sets according to regional tag data sets is represented, and talent tag data sets/>, according to talent tag data setsThe blue-collar talents are marked in a batched and classified mode according to different skill data, work age data and frequent region data, a unified tag data set standard is fixed, and the efficiency of subsequent matching positions is higher;
The enterprise management module comprises a job issuing unit and a skill alignment unit, wherein the job issuing unit acquires a job data set through a file transmission interface or an AI intelligent video device, an enterprise manager inputs a job recruitment document through a connection file transmission interface or inputs job recruitment content through video recording of the AI intelligent video device, recruitment information is rapidly issued through the AI intelligent video device, the enterprise management module is suitable for urgent job recruitment of an enterprise, video explanation job content, skill requirements, work age and region requirements are clearer, subsequent solicited interview communication efficiency is higher, the job data set is transmitted to the skill alignment unit through a network after numbering, and the job data set is numbered as 、/>、/>、.../>The serial number corresponds to all position information stored in the position release unit by enterprise management personnel, and the skill alignment unit generates a demand label data set/>, according to the position data set, the label data set and the classification by the skill alignment unitThe enterprise management module is connected with the resource matching module through the network, and the classification generation algorithm formula of the enterprise management module is as follows:
；
In the formula (i), Representing demand label data set,/>Representing job skill tag data generated by classifying a job dataset according to a skill tag dataset,/>Representing job age tag data generated by classifying a job data set according to the job age tag data set,/>Representing job region tag data generated by classifying a job data set according to the region tag data set, and tagging the data set/>, according to requirementsThe office positions of enterprises are marked in batches according to different skill requirements, work age requirements and frequent region requirements, unified tag data set standards are fixed, and the efficiency of subsequent matching of blue-collar talents is higher;
The resource matching module comprises a supply arrangement unit, a demand arrangement unit and a person post matching unit, wherein the supply arrangement unit is used for marking a data set according to talents The method comprises the steps of sequentially arranging resume data sets, wherein talent resume sequences with a large number of labels in the resume data sets are forward, blue-collar correspondence skills with a large number of labels are strong, job-seeking upward compatibility is high, various enterprise positions are adapted, attractiveness to enterprise management personnel is strong, human resource management matching efficiency is high, data are transmitted to a post matching unit, and a demand arrangement unit performs/>, according to a demand label data setThe job data sets are sequentially arranged, recruitment positions with a large number of labels in the job data sets are positioned in front, the positions with a large number of labels correspond to high salary, recruitment downward compatibility is high, multiple blue-collar people are adapted, job-seeking attraction is high, human resource management matching efficiency is high, data are transmitted to a person post matching unit, and the person post matching unit performs/>, according to the person talent label data setDemand label dataset/>The resume data set and the job data set are calculated to generate a matching set/>The resource matching module is connected with the job-seeking interview module through the network, and the calculation formula is as follows:
；
In the formula (i), Representing a matching set,/>Representing the union portion of a specified talent tag dataset and a resume dataset,/>Representing a union portion of the specified demand label dataset and the job dataset,Representing blue-collar talents and enterprise job data sets matched by person post according to label data sets, and/>, according to the matched setsThe system can quickly match talents with enterprise positions, and has high human resource management matching efficiency;
The job hunting interview module is connected with the AI blue-collar intelligent service platform through a network and comprises a talent interview unit and an enterprise recruitment unit, and blue-collar crowd sets a key interview model through a user side Talent interview unit based on the focused interview model/>For matching set/>Scoring the matched enterprise position data, and under the condition that the full score is 100 points, talent label data group/>And demand label dataset/>The matching similarity is high, the labels are the same in number, the corresponding enterprises are high in score, flexible service is more humanized, the flexible service is transmitted back to the user side through the network, the enterprises are waited to communicate with the enterprises for interviews after screening, and enterprise management staff set key recruitment models/>, through the enterprise sideThe enterprise recruitment unit recruits the model according to the key pointsFor matching set/>Scoring the matched blue-collar talent data, and under the condition that the score is 100, marking the talent label data group/>And demand label dataset/>The matching similarity is high, the labels are the same in number and correspond to the blue collars with high scores, the flexible service matching efficiency is higher, the flexible service matching efficiency is transmitted back to the enterprise terminal through the network, and the blue collars are invited to be interviewed after the screening.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. Human resource management system based on AI blue-collar intelligent service platform, its characterized in that: the system comprises a talent management module, an enterprise management module, a resource matching module and a job hunting interview module;
the talent management module comprises a talent resume unit and a label classification unit, wherein the talent resume unit collects resume data sets through a file transmission interface or an AI intelligent voice device, the resume data sets are transmitted to the label classification unit through a network after numbered, the label classification unit establishes a label data set through a network connection database and numbered, and the label classification unit combines the label data sets according to the resume data sets to generate talent label data sets in a classified manner The talent management module is connected with the resource matching module through a network;
The enterprise management module comprises a job issuing unit and a skill alignment unit, wherein the job issuing unit collects a job data set through a file transmission interface or an AI intelligent video device, and transmits the job data set to the skill alignment unit through a network after numbering, and the skill alignment unit generates a demand label data set according to the job data set, combines a label data set and classifies the demand label data set The enterprise management module is connected with the resource matching module through a network;
the resource matching module comprises a supply arrangement unit, a demand arrangement unit and a person post matching unit, wherein the supply arrangement unit is used for marking a data set according to talents Sequentially arranging resume data sets and transmitting the data to a post matching unit, wherein the requirement arranging unit is used for labeling data sets/>, according to requirementsSequentially arranging the job position data sets and transmitting the data to a post matching unit, wherein the post matching unit performs the post matching according to the talent label data set/>Demand label dataset/>The resume data set and the job data set are calculated to generate a matching set/>The resource matching module is connected with the job-seeking interview module through a network;
The job-seeking interview module is connected with the AI blue-collar intelligent service platform through a network, comprises a talent interview unit and an enterprise recruitment unit, and is provided with a key interview model through a user side The talent interview unit is based on a key interview model/>For matching set/>Grading, and transmitting the grading back to the user side through a network, waiting for the screening and then communicating with the enterprise for interviews, and setting a key recruitment model/>, by an enterprise manager through the enterprise sideThe enterprise recruitment unit performs/>, according to the key recruitment modelFor matching set/>Scoring is carried out, the scoring is transmitted back to the enterprise end through the network, and the blue lead is invited to carry out interview after waiting to be screened.
2. The AI-based intelligent service platform human resource management system of claim 1, wherein: inputting a resume document through a connection file transmission interface or inputting resume content through online voice of a voice device to form a resume data set, wherein the talent resume unit numbers the resume data set according to the resume data set characteristics, and the resume data set numbers are as follows、、/>、.../>。
3. The AI-based intelligent service platform human resource management system of claim 1, wherein: the label data set consists of a skill label data set, a work age label data set and a region label data set, the label classification unit numbers the skill label data set, the work age label data set and the region label data set according to the characteristics of the label data set, and the label data set numbers are as follows、/>And/>。
4. The AI-based blue-neck intelligent service platform human resource management system according to claim 3, wherein: the label classification unit combines the label data set according to the resume data set to generate talent label data set in a classification wayThe classification generation algorithm formula is as follows:
；
In the formula (i), Representing talent tag data group,/>Talent skill label data representing the classification of a resume dataset according to a skill label dataset,/>Talent age tag data representing classification of resume data sets based on age tag data setsAnd the talent regional tag data is generated by classifying the resume data set according to the regional tag data set.
5. The AI-based intelligent service platform human resource management system of claim 1, wherein: the enterprise manager inputs a job recruitment document through a connection file transmission interface or records and inputs job recruitment content through an AI intelligent video device to form a job data set, the job issuing unit numbers the job data set according to the characteristic of the job data set, and the number of the job data set is、/>、/>、.../>。
6. The AI-based intelligent service platform human resource management system of claim 5, wherein: the skill alignment unit generates a demand label data set according to the job position data set and the label data set in a classified mannerThe classification generation algorithm formula is as follows:
；
In the formula (i), Representing demand label data set,/>Representing job skill tag data generated by classifying a job dataset according to a skill tag dataset,/>Representing job age tag data generated by classifying a job data set according to the job age tag data set,/>And the position regional label data are generated by classifying the position data set according to the regional label data set.
7. The AI-based intelligent service platform human resource management system of claim 1, wherein: the supply arrangement unit is used for arranging the label data group according to talentsSequentially arranging the resume data sets, wherein the resume data sets have a plurality of tags, the talent resume sequence is front, and the demand arrangement unit is used for labeling the data sets/>, according to demandsAnd sequentially arranging the job data sets, wherein the recruitment positions with a large number of labels in the job data sets are positioned at the front.
8. The AI-based intelligent service platform human resource management system of claim 7, wherein: the person post matching unit is used for marking the data group according to the person talentsDemand label dataset/>The resume data set and the job data set are calculated to generate a matching set/>The calculation formula is as follows:
；
In the formula (i), Representing a matching set,/>Representing the union portion of a specified talent tag dataset and a resume dataset,/>Representing a union portion of the specified demand label dataset and the job dataset,Representing a blue-collar talent and business job data set that performs a person-post match based on the tag data set.
9. The AI-based blue-neck intelligent service platform human resource management system of claim 8, wherein: the talent interview unit performs interview according to the key interview modelFor matching set/>Scoring the matched enterprise job data, talent tag data set/>And demand label dataset/>The matching similarity is high, and the labels are the same in number and correspond to enterprises with high scores.
10. The AI-based blue-neck intelligent service platform human resource management system of claim 8, wherein: the enterprise recruitment unit is used for recruiting the enterprise according to the key recruitment modelFor matching set/>Scoring the matched blue-collar talent data, and marking the talent label data group/>And demand label data/>The group matching similarity is high, and the same number of tags corresponds to high blue collar scores.
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| CN108305047A (en) * | 2018-01-31 | 2018-07-20 | 合肥和钧正策信息技术有限公司 | A kind of talent's big data enterprises service system |
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| CN112765235A (en) * | 2021-01-21 | 2021-05-07 | 盐城志娟网络科技有限公司 | Human resource intelligent management system based on feature recognition and big data analysis and cloud management server |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108305047A (en) * | 2018-01-31 | 2018-07-20 | 合肥和钧正策信息技术有限公司 | A kind of talent's big data enterprises service system |
| CN111144781A (en) * | 2019-12-31 | 2020-05-12 | 江苏德尔斐数字科技有限公司 | Intelligent talent evaluation screening method based on cloud data |
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