CN111612431A - Manpower matching method and system based on big data - Google Patents
Manpower matching method and system based on big data Download PDFInfo
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- CN111612431A CN111612431A CN202010456752.4A CN202010456752A CN111612431A CN 111612431 A CN111612431 A CN 111612431A CN 202010456752 A CN202010456752 A CN 202010456752A CN 111612431 A CN111612431 A CN 111612431A
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- G06Q10/105—Human resources
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- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
- G06Q10/063112—Skill-based matching of a person or a group to a task
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Abstract
The invention discloses a manpower matching method and system based on big data, belonging to the field of manpower resource matching; the method comprises the steps of obtaining post characteristic data of an enterprise and similar post data of the same industry through a data obtaining module, and performing model training by using a machine learning algorithm to generate a data model between posts and skills; acquire user occupation development information through user registration, according to machine learning algorithm, carry out the model training, generate post development route and skill topological graph, job seeker accessible job seeker learning module learns corresponding post skill, and record job seeker's occupation route and study route, through artificial intelligence algorithm, match job seeker occupation route and study route and enterprise post development demand characteristic, thereby for the job seeker of enterprise recommendation compound post development demand, can reduce enterprise staff's recruitment cost effectively, and shorten job seeker's period of seeking employment.
Description
Technical Field
The invention belongs to the technical field of human resource matching, and particularly relates to a human matching method and system based on big data.
Background
The job seeker seeks to create material wealth and mental wealth for enterprises by utilizing knowledge and skills learned by the job seeker, obtains reasonable rewards, and is used as a way of material life sources.
In the current job hunting mode, the resume data and the skill data of the job hunter are generally filled by the job hunter, the authenticity of the resume data and the skill data needs to be considered, the condition that the skills of job hunting staff of an enterprise are not matched is easily caused, the job hunting cost of the enterprise is increased, and the job hunting efficiency of the job hunting staff and the job hunting efficiency of the enterprise are influenced.
Disclosure of Invention
The present invention provides a method and a system for human matching based on big data, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
a method of human matching based on big data, the method comprising the steps of:
s1, acquiring post characteristic data of an enterprise and similar post characteristic data of the same industry;
s2, performing model training through a machine learning algorithm to generate a data model between a post and a skill;
s3, filling by a registered user, and acquiring the professional development information of the user;
s4, performing model training through a machine learning algorithm to generate professional development paths and skill topological diagrams of different industries;
and S5, recording the occupation path and the learning path of the job seeker, and recommending the job seeker meeting the post development requirement for the enterprise through an artificial intelligence algorithm.
Preferably, in S1, the position characteristic data and the position characteristic data similar to the same industry are obtained by using any one or two of a web crawler technology and an enterprise cooperation method.
Preferably, the post characteristic data comprises product characteristics, industry characteristics and post skill requirement characteristic data.
Preferably, the similar position characteristic data of the same industry comprises requirement characteristic data and training course characteristic data in a company.
In addition, the invention also provides a manpower matching system based on big data, which is used for executing the method to match job seekers with corresponding skills for the enterprise posts; the system comprises a data acquisition module, a machine learning module, a job seeker learning module and a post talent matching module, wherein the data acquisition module is used for acquiring and storing product characteristics, industry characteristics and skill demand characteristics of enterprises, similar post demand characteristics in the same industry and training course characteristic data in companies in the same industry, the machine learning module is used for calling the data acquired by the data acquisition module to perform model training and generating graph-theory topological relations among career development paths, posts and skills, the job seeker learning module is used for providing and recommending skill course learning paths for job seekers and storing skill learning records, and the post talent matching module is used for matching job seekers with corresponding skills for the enterprise posts according to the graph-theory topological relations among the career development paths, the posts and the skills.
Preferably, the post talent matching module matches job seekers with corresponding skills for the enterprise posts through a machine learning prediction model.
The invention can effectively and accurately match and recommend job seekers with the skills required by the posts for the enterprise posts, effectively reduce the recruitment cost of enterprise workers and shorten the job hunting period of the job seekers.
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FIG. 1 is an architecture diagram of a human matching system based on big data;
FIG. 2 is a flow chart of the steps of a method for human matching based on big data.
Detailed Description
The present invention will be further described with reference to the following examples.
The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention. The conditions in the embodiments can be further adjusted according to specific conditions, and simple modifications of the method of the present invention based on the concept of the present invention are within the scope of the claimed invention.
As shown in FIG. 1, the invention provides a human matching system based on big data, which comprises a data acquisition module, a machine learning module, a job seeker learning module and a post talent matching module;
the data acquisition module is used for acquiring and storing product characteristics, industry characteristics and skill demand characteristics of enterprises, similar post demand characteristics of the same industry and training course characteristic data in companies of the same industry from the Internet and cooperative enterprises;
the machine learning module is used for calling the data acquired by the data acquisition module to perform model training and generating graph theory topological relations among career development paths, posts and skills;
the job seeker learning module is used for providing and recommending a skill course learning path for the job seeker and storing a skill learning record;
and the post talent matching module is used for matching job seekers with corresponding skills for the enterprise posts according to the career development path, the post and the graph and theory topological relation among the skills.
The post talent matching module matches job seekers with corresponding skills for the enterprise posts through a machine learning prediction model.
When recommending a job seeker with the skill required by the position for the enterprise, as shown in fig. 2, the system performs the following steps:
s1, acquiring product characteristics, industry characteristics and post skill requirement characteristics of an enterprise, similar post requirement characteristics of the same industry and training course characteristic data in a company through a web crawler technology and enterprise cooperation mode;
s2, performing model training through a machine learning algorithm to generate a data model between a post and a skill;
s3, filling by a registered user, and acquiring the professional development information of the user;
s4, performing model training through a machine learning algorithm to generate professional development paths and skill topological diagrams of different industries;
and S5, recording the occupation path and the learning path of the job seeker, and recommending the job seeker meeting the post development requirement for the enterprise through an artificial intelligence algorithm.
The method comprises the steps of obtaining post characteristic data of an enterprise and similar post data of the same industry through a data obtaining module, and performing model training by using a machine learning algorithm to generate a data model between posts and skills; acquire user occupation development information through user registration, according to machine learning algorithm, carry out the model training, generate post development route and skill topological graph, job seeker accessible job seeker learning module learns corresponding post skill, and record job seeker's occupation route and study route, through artificial intelligence algorithm, match job seeker occupation route and study route and enterprise post development demand characteristic, thereby for the job seeker of enterprise recommendation compound post development demand, can reduce enterprise staff's recruitment cost effectively, and shorten job seeker's period of seeking employment.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A method for matching manpower based on big data is characterized by comprising the following steps:
s1, acquiring post characteristic data of an enterprise and similar post characteristic data of the same industry;
s2, performing model training through a machine learning algorithm to generate a data model between a post and a skill;
s3, filling by a registered user, and acquiring the professional development information of the user;
s4, performing model training through a machine learning algorithm to generate professional development paths and skill topological diagrams of different industries;
and S5, recording the occupation path and the learning path of the job seeker, and recommending the job seeker meeting the post development requirement for the enterprise through an artificial intelligence algorithm.
2. The big-data-based human matching method according to claim 1, wherein in the step S1, the acquisition of the position characteristic data and the similar position characteristic data in the same industry adopts any one or both of a web crawler technology and an enterprise cooperation mode.
3. The big-data based human matching method as claimed in claim 2, wherein the post characteristic data comprises product characteristic, industry characteristic and post skill requirement characteristic data.
4. The big-data based human matching method as claimed in claim 2, wherein the same-industry similar-position feature data comprises requirement feature and in-company training course feature data.
5. A big data based human matching system, which is used for executing the method of any one of claims 1-4 to match job seekers with corresponding skills for enterprise posts; the system comprises a data acquisition module, a machine learning module, a job seeker learning module and a post talent matching module;
the data acquisition module is used for acquiring and storing product characteristics, industry characteristics and skill demand characteristics of enterprises, similar post demand characteristics of the same industry and training course characteristic data in companies of the same industry from the Internet and cooperative enterprises;
the machine learning module is used for calling the data acquired by the data acquisition module to perform model training and generating graph theory topological relations among career development paths, posts and skills;
the job seeker learning module is used for providing and recommending a skill course learning path for the job seeker and storing a skill learning record;
and the post talent matching module is used for matching job seekers with corresponding skills for the enterprise posts according to the career development path, the post and the graph and theory topological relation among the skills.
6. The big-data based human matching system as claimed in claim 5, wherein the post talent matching module matches job seekers with corresponding skills to the enterprise post through a machine learning prediction model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202010456752.4A CN111612431A (en) | 2020-05-26 | 2020-05-26 | Manpower matching method and system based on big data |
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| CN202010456752.4A CN111612431A (en) | 2020-05-26 | 2020-05-26 | Manpower matching method and system based on big data |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112966956A (en) * | 2021-03-18 | 2021-06-15 | 四川跨客通科技有限公司 | Professional ability assessment system and method based on union link contract technology |
| CN114168819A (en) * | 2022-02-14 | 2022-03-11 | 北京大学 | Post matching method and device based on graph neural network |
| CN116993311A (en) * | 2023-09-21 | 2023-11-03 | 浙江厚雪网络科技有限公司 | Human resource information retrieval system based on information matching technology |
-
2020
- 2020-05-26 CN CN202010456752.4A patent/CN111612431A/en not_active Withdrawn
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112966956A (en) * | 2021-03-18 | 2021-06-15 | 四川跨客通科技有限公司 | Professional ability assessment system and method based on union link contract technology |
| CN114168819A (en) * | 2022-02-14 | 2022-03-11 | 北京大学 | Post matching method and device based on graph neural network |
| CN114168819B (en) * | 2022-02-14 | 2022-07-12 | 北京大学 | Post matching method and device based on graph neural network |
| CN116993311A (en) * | 2023-09-21 | 2023-11-03 | 浙江厚雪网络科技有限公司 | Human resource information retrieval system based on information matching technology |
| CN116993311B (en) * | 2023-09-21 | 2023-12-19 | 浙江厚雪网络科技有限公司 | Human resource information retrieval system based on information matching technology |
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