CN106600213B - Intelligent management system and method for personal resume - Google Patents
Intelligent management system and method for personal resume Download PDFInfo
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Abstract
The invention provides an intelligent management system and method of personal resume, wherein the system comprises a personal resume template establishing module, a user data input module, a recommended enterprise searching and enterprise data acquisition module, a keyword extraction module and a personal resume recombination module; the personal resume template establishing module is used for establishing a personal resume standard template and carrying out industry marking on the personal resume standard template; the user data input module is used for inputting user employment interest data, employment direction data and employment field data; inputting personal resume data of the user; the recommended enterprise searching and enterprise data collecting module searches recommended enterprises from the Internet through a web text crawler technology, outputs a recommended enterprise list and collects enterprise data of the recommended enterprises; the invention enables personal resume data filled by users to be more matched with the employment standard of enterprises; the employment success rate of the user is improved, and convenience is provided for enterprise recruiting talents.
Description
Technical Field
The invention relates to the technical field of personal resume management, in particular to a personal resume management system and method based on artificial intelligence.
Background
The personal resume is an important medium for talents to find work and enterprises to discover talents, the existing personal resume generally comprises education, employment backgrounds and descriptions of personal characteristics, and the personal resume has two defects: on one hand, the personal resume data is not standard due to the fact that the personal resume formats are not uniform, and the personal resume data cannot be analyzed and managed efficiently by using artificial intelligence, so that a user cannot fill in resume contents to the maximum extent according to the characteristics and requirements of different industries.
On the other hand, the existing personal resume can not dynamically adjust the content of the personal resume according to the specific talent requirements of different enterprises, so that the problem that the talent quality is not matched with the enterprise requirements is caused, and the talents can not be well employment and the enterprises can not recruit talents suitable for enterprise development.
Disclosure of Invention
The invention provides an intelligent management system and method of personal resume, which enable the personal resume data to become standard data through establishing a personal resume template, and are convenient for extracting keywords of the personal resume data; the personal resume data filled by the user is more matched with the employment standard of the enterprise; the employment success rate of the user is improved, and convenience is provided for enterprise recruiting talents.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
the invention provides an intelligent management system of a personal resume, which comprises a personal resume template establishing module, a user data input module, a recommended enterprise searching and enterprise data acquisition module, a keyword extraction module and a personal resume recombination module;
the personal resume template establishing module is used for establishing a personal resume standard template with a corresponding unit composition structure according to industry classification and carrying out industry marking on the personal resume standard template;
the user data input module is used for inputting user employment interest data, employment direction data and employment field data; inputting personal resume data of a user according to the personal resume standard template;
the recommended enterprise searching and enterprise data acquisition module is used for searching recommended enterprises from the Internet through a web text crawler technology according to employment interest data, employment direction data and employment field data input by a user, outputting a recommended enterprise list and acquiring enterprise data of the recommended enterprises;
the keyword extraction module is used for extracting keywords from personal resume data input by a user and acquired enterprise data of the recommended enterprise through a TF-IDF algorithm to form a personal resume keyword vector and an enterprise data keyword vector;
the personal resume recombining module is used for calculating the similarity between the personal resume keyword vector and the keywords in the enterprise data keyword vector, sorting the enterprises from large to small according to the similarity, and outputting a sorting list of the enterprises; and recombining the personal resume data input by the user according to the enterprise data keywords of each recommended enterprise and recommending the recombined personal resume data to the enterprise.
Further, the TF-IDF algorithm of the keyword extraction module calculates TF-IDF values one by one for words appearing in enterprise data of the user personal resume and the recommended enterprise, and performs sorting from large to small according to the calculated TF-IDF values to form a keyword vector.
Still further, the enterprise data collected from the internet for recommending the enterprise comprises industry competition data of the industry to which the enterprise belongs, product and service data of the enterprise, background data of core personnel of the enterprise, and recruitment data of the enterprise.
Still further, the unit composition structure of the personal resume standard template is as follows: an education background filling unit and a employment experience filling unit.
The invention provides a personal resume intelligent management method, which comprises a personal resume template establishing step, a user data input step, a keyword extraction step, a recommended enterprise searching and enterprise data acquisition step and a personal resume recombining step;
the personal resume template establishing step comprises the following steps: establishing a personal resume standard template with a corresponding unit composition structure according to industry classification, and carrying out industry marking on the personal resume standard template;
the user data input step includes: the user inputs employment interest data, employment direction data and employment field data of the user; inputting personal resume data of a user according to the personal resume standard template;
the steps of recommending enterprise searching and acquiring enterprise data comprise: searching recommended enterprises from the internet through a web text crawler technology according to employment interest data, employment direction data and employment field data input by a user, outputting a recommended enterprise list and collecting enterprise data of the recommended enterprises;
the keyword extraction step comprises: performing keyword extraction on personal resume data input by a user and acquired enterprise data of the recommended enterprise through a TF-IDF algorithm to form a personal resume keyword vector and an enterprise data keyword vector;
the personal resume reorganization step comprises the following steps: and calculating the similarity between the personal resume keyword vectors and the keywords in the enterprise data keyword vectors, sequencing the enterprises from large to small according to the similarity, outputting a sequencing list of the enterprises, recombining the personal resume data input by the user according to the enterprise data keywords of each recommended enterprise, and recommending the personal resume data to the enterprise.
Further, the TF-IDF algorithm of the keyword extraction step calculates TF-IDF values one by one for words appearing in enterprise data of the user personal resume and the recommended enterprise, and performs sorting from large to small according to the calculated TF-IDF values to form a keyword vector.
Still further, the enterprise data collected from the internet for recommending the enterprise comprises industry competition data of the industry to which the enterprise belongs, product and service data of the enterprise, background data of core personnel of the enterprise, and recruitment data of the enterprise.
Still further, the unit composition structure of the personal resume standard template is as follows: an education background filling unit and a employment experience filling unit.
According to the personal resume intelligent management system and method provided by the invention, the personal resume data is made to be the standard data through the establishment of the personal resume template, so that the problems that the personal resume in the prior art cannot reflect the characteristics and the requirements of different industries to the maximum extent, and the personal resume data is not standard and cannot be analyzed and managed efficiently by using artificial intelligence due to the non-uniform format of the personal resume are solved.
The recommended enterprise searching and enterprise data acquisition module searches recommended enterprises from the Internet through a web text crawler technology according to employment interest data, employment direction data and employment field data input by a user and outputs a recommended enterprise list, so that the user can more accurately know enterprises related to the employment interest, the employment direction and the employment field; the system selects a personal resume standard template matched with the employment interest, the employment direction and the employment field of a user from the personal resume standard templates subjected to the industry marking, and the user inputs personal resume data of the user according to the personal resume standard template; the personal resume data filled by the user is more matched with the employment standard of the enterprise; the employment success rate of the user is improved;
the system also enables a user to more specifically know enterprise data related to the employment interest, employment direction and employment field of the user by collecting enterprise data of the recommended enterprise, including industry competition data of the industry to which the enterprise belongs, product and service data of the enterprise, background data of core personnel of the enterprise and recruitment data of the enterprise, and performs keyword extraction on personal resume data input by the user and the collected enterprise data of the recommended enterprise through a TF-IDF algorithm of the keyword extraction module to form a personal resume keyword vector and an enterprise data keyword vector; then calculating the similarity between the personal resume keyword vector and the keywords in the enterprise data keyword vector, sorting the enterprises according to the similarity from big to small, and outputting a sorting list of the enterprises; the user can obtain the enterprise which is most matched with the personal resume of the user so far according to the sequencing list of the enterprises;
moreover, the enterprise data keyword vector provides dynamic information required by the selected industrial talents for the user, and because the user can dynamically fill the education background and employment experience of the user in the education background filling unit and the employment experience filling unit of the system, and can also compare the recommended enterprise list output from the system and the collected enterprise data of the recommended enterprise with the personal resume content to know the defects of the knowledge structure or capability of the user, the personal resume filled into the system by the user is continuously enriched by continuously learning or receiving training, so that the user can better prepare for the work of the employment apparatus, the success rate of employment of the user is improved, on the other hand, the system recombines the personal resume data input by the user according to the enterprise keywords extracted from the enterprise data and recommends the personal resume data to the enterprise, the enterprise also obtains talents more suitable for enterprise development, and convenience is provided for enterprise recruitment of talents. The problem that the personal resume in the prior art cannot dynamically adjust the content of the personal resume according to the specific talent requirements of different enterprises, so that the talent quality is unmatched with the enterprise requirements is solved, and meanwhile, the guidance from the enterprise requirements is provided for the user to improve the self quality.
Drawings
FIG. 1 is a schematic structural diagram of an intelligent management system for personal resumes according to an embodiment of the present invention;
FIG. 2 is a block diagram illustrating steps of a method for intelligent management of personal resumes, according to an embodiment of the present invention;
FIG. 3 is a block diagram of the steps of inputting user data in a method for intelligent management of personal resumes according to an embodiment of the present invention;
fig. 4 is a block diagram illustrating steps of enterprise data collection of an intelligent personal resume management method according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described in detail with reference to the accompanying drawings, which are for reference and illustrative purposes only and are not intended to limit the scope of the invention.
As shown in fig. 1, an aspect of the present invention provides an intelligent personal resume management system, which includes a personal resume template creating module, a user data input module, a recommended enterprise search and enterprise data collecting module, a keyword extracting module, and a personal resume restructuring module;
the personal resume template establishing module is used for establishing a personal resume standard template with a corresponding unit composition structure according to industry classification and carrying out industry marking on the personal resume standard template;
the user data input module is used for inputting user employment interest data, employment direction data and employment field data; inputting personal resume data of a user according to the personal resume standard template; the personal resume data is standard data, so that the extraction of keywords of the personal resume is facilitated; the personal resume data filled by the user is more matched with the employment standard of the enterprise;
the recommended enterprise searching and enterprise data acquisition module is used for searching recommended enterprises from the Internet through a web text crawler technology according to employment interest data, employment direction data and employment field data input by a user, outputting a recommended enterprise list and acquiring enterprise data of the recommended enterprises; specifically, the crawler technology in the script software package is adopted to mine big data in the internet and search enterprise data of recommended enterprises in the internet. The enterprise data comprises industry competition data of the industry to which the enterprise belongs, product and service data of the enterprise, background data of core personnel of the enterprise and recruitment data of the enterprise.
The keyword extraction module is used for extracting keywords from personal resume data input by a user and acquired enterprise data of the recommended enterprise through a TF-IDF algorithm to form a personal resume keyword vector and an enterprise data keyword vector;
the personal resume recombining module is used for calculating the similarity between the personal resume keyword vectors and the keywords in each recommended enterprise data keyword vector, sorting the enterprises from large to small according to the similarity, outputting a sorting list of the enterprises, recombining the personal resume data input by the user according to the enterprise data keywords of each recommended enterprise, and recommending the recombined personal resume data to the enterprises.
It should be noted that: the similarity between the personal resume keyword vector and the keywords in the enterprise data keyword vector of each recommended enterprise is calculated by adopting the Euclidean distance, the personal resume keyword vector and all words (non-repeated) in the selected enterprise data keyword vector form a vector, the word frequency of the ith word in the personal resume keyword vector is taken as xi, the word frequency in the data keyword vector of the selected enterprise is taken as yi, and the Euclidean distance is calculated by adopting the following formula:
preferably, the TF-IDF algorithm of the keyword extraction module calculates TF-IDF values one by one for words appearing in enterprise data of the user personal resume and the recommended enterprise, and performs sorting from large to small according to the calculated TF-IDF values to form a keyword vector. Specifically, the keyword extraction is realized by adopting the keyword extraction function of the jiebaR software package.
Preferably, the enterprise data collected from the internet for recommending the enterprise comprises industry competition data of an industry to which the enterprise belongs, product and service data of the enterprise, background data of core personnel of the enterprise, and recruitment data of the enterprise.
Preferably, the unit composition structure of the personal resume standard template is as follows: the education background filling unit and the employment experience filling unit or other data filling units. The education background filling unit is used for collecting education background data of graduation schools and academic specialties of the users, and the employment experience filling unit is used for collecting work histories of the users, including position data and work content data of work.
Fig. 2 is a block diagram illustrating steps of an intelligent management method for a personal resume according to an embodiment of the present invention, and another aspect of the present invention provides an intelligent management method for a personal resume, including a personal resume template establishing step, a user data inputting step, an enterprise recommending and data collecting step, a keyword extracting step, and a personal resume recombining step;
the personal resume template establishing module is used for establishing a personal resume standard template with a corresponding unit composition structure according to industry classification and carrying out industry marking on the personal resume standard template;
the user data input step includes: the user inputs employment interest data, employment direction data and employment field data of the user; inputting personal resume data of a user according to the personal resume standard template;
the steps of recommending enterprise searching and acquiring enterprise data comprise: searching recommended enterprises from the internet through a web text crawler technology according to employment interest data, employment direction data and employment field data input by a user, outputting a recommended enterprise list and collecting enterprise data of the recommended enterprises; specifically, the crawler technology in the Scapy software package is adopted to search enterprise data of recommended enterprises in the Internet.
The keyword extraction step comprises: performing keyword extraction on personal resume data input by a user and acquired enterprise data of the recommended enterprise through a TF-IDF algorithm to form a personal resume keyword vector and an enterprise data keyword vector;
the personal resume reorganization step comprises the following steps: and calculating the similarity between the personal resume keyword vectors and the keywords in the enterprise data keyword vectors, sequencing the enterprises from large to small according to the similarity, outputting a sequencing list of the enterprises, recombining the personal resume data input by the user according to the enterprise data keywords of each recommended enterprise, and recommending the personal resume data to the enterprise.
It should be noted that: the similarity between the personal resume keyword vector and the keywords in each recommended enterprise data keyword vector is calculated by adopting the Euclidean distance, the personal resume keyword vector and all words (non-repeated) in the selected enterprise data keyword vector form a vector, the word frequency of the ith word in the personal resume keyword vector is taken as xi, the word frequency in the selected enterprise data keyword vector is taken as yi, and the Euclidean distance is calculated by adopting the following formula:
preferably, the TF-IDF algorithm of the keyword extraction step calculates TF-IDF values one by one for words appearing in enterprise data of the user personal resume and the recommended enterprise, and performs sorting from large to small according to the calculated TF-IDF values to form a keyword vector. Specifically, the keyword extraction is realized by adopting the keyword extraction function of the jiebaR software package.
As shown in fig. 3, preferably, the unit composition structure of the personal resume standard template is: the education background filling unit and the employment experience filling unit or other data filling units. The education background filling unit is used for collecting education background data of graduation schools and academic specialties of the users, and the employment experience filling unit is used for collecting work histories of the users, including position data and work content data of work.
As shown in fig. 4, preferably, the enterprise data collected from the internet for the relevant enterprise includes industry competition data of the industry to which the enterprise belongs, product and service data of the enterprise, background data of core personnel of the enterprise, and recruitment data of the enterprise.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention.
Claims (8)
1. An intelligent personal resume management system, characterized in that: the system comprises a personal resume template establishing module, a user data input module, a recommended enterprise searching and enterprise data acquisition module, a keyword extraction module and a personal resume recombination module;
the personal resume template establishing module is used for establishing a personal resume standard template with a corresponding unit composition structure according to industry classification and carrying out industry marking on the personal resume standard template;
the user data input module is used for inputting user employment interest data, employment direction data and employment field data; inputting personal resume data of a user according to the personal resume standard template;
the recommended enterprise searching and enterprise data acquisition module is used for searching recommended enterprises from the Internet through a web text crawler technology according to employment interest data, employment direction data and employment field data input by a user, outputting a recommended enterprise list and acquiring enterprise data of the recommended enterprises;
the keyword extraction module is used for extracting keywords from personal resume data input by a user and acquired enterprise data of the recommended enterprise through a TF-IDF algorithm to form a personal resume keyword vector and an enterprise data keyword vector;
the personal resume recombining module is used for calculating the similarity between the personal resume keyword vector and the keywords in the enterprise data keyword vector, sorting the enterprises from large to small according to the similarity, and outputting a sorting list of the enterprises; and recombining the personal resume data input by the user according to the enterprise data keywords of each recommended enterprise and recommending the recombined personal resume data to the enterprise.
2. The intelligent personal resume management system of claim 1, wherein: and the TF-IDF algorithm of the keyword extraction module calculates TF-IDF values one by one for words appearing in enterprise data of the user personal resume and the recommended enterprise, and performs sorting from large to small according to the calculated TF-IDF values to form a keyword vector.
3. The intelligent personal resume management system of claim 1, wherein: the enterprise data collected from the Internet for recommending the enterprise comprises industry competition data of the industry to which the enterprise belongs, product and service data of the enterprise, background data of core personnel of the enterprise and recruitment data of the enterprise.
4. The intelligent personal resume management system of claim 1, wherein: the unit composition structure of the personal resume standard template is as follows: an education background filling unit and a employment experience filling unit.
5. An intelligent management method for personal resume is characterized in that: the method comprises a personal resume template establishing step, a user data input step, a keyword extraction step, a recommended enterprise searching and enterprise data acquisition step and a personal resume recombining step;
the personal resume template establishing step comprises the following steps: establishing a personal resume standard template with a corresponding unit composition structure according to industry classification, and carrying out industry marking on the personal resume standard template;
the user data input step includes: the user inputs employment interest data, employment direction data and employment field data of the user; inputting personal resume data of a user according to the personal resume standard template;
the steps of recommending enterprise searching and acquiring enterprise data comprise: searching recommended enterprises from the internet through a web text crawler technology according to employment interest data, employment direction data and employment field data input by a user, outputting a recommended enterprise list and collecting enterprise data of the recommended enterprises;
the keyword extraction step comprises: performing keyword extraction on personal resume data input by a user and acquired enterprise data of the recommended enterprise through a TF-IDF algorithm to form a personal resume keyword vector and an enterprise data keyword vector;
the personal resume reorganization step comprises the following steps: and calculating the similarity between the personal resume keyword vectors and the keywords in the enterprise data keyword vectors, sequencing the enterprises from large to small according to the similarity, outputting a sequencing list of the enterprises, recombining the personal resume data input by the user according to the enterprise data keywords of each recommended enterprise, and recommending the personal resume data to the enterprise.
6. The intelligent personal resume management method of claim 5, wherein: and the TF-IDF algorithm of the keyword extraction step calculates TF-IDF values one by one for words appearing in enterprise data of the user personal resume and the recommended enterprise, and performs sorting from large to small according to the calculated TF-IDF values to form a keyword vector.
7. The intelligent personal resume management method of claim 5, wherein: the enterprise data collected from the Internet for recommending the enterprise comprises industry competition data of the industry to which the enterprise belongs, product and service data of the enterprise, background data of core personnel of the enterprise and recruitment data of the enterprise.
8. The intelligent personal resume management method of claim 5, wherein: the unit composition structure of the personal resume standard template is as follows: an education background filling unit and a employment experience filling unit.
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| CN108038655A (en) * | 2017-11-01 | 2018-05-15 | 平安科技（深圳）有限公司 | Recommendation method, application server and the computer-readable recording medium of department's demand |
| CN108765219A (en) * | 2018-05-11 | 2018-11-06 | 重庆工商职业学院 | A kind of job transfers system and its control method |
| CN108733827A (en) * | 2018-05-24 | 2018-11-02 | 佛山市轻遣网络有限公司 | A kind of recruitment information acquisition methods outside recruitment website and system |
| CN108845980B (en) * | 2018-05-30 | 2022-08-09 | 深圳市元征科技股份有限公司 | Resume generation method, system, device and computer readable storage medium |
| CN110232646A (en) * | 2019-06-11 | 2019-09-13 | 东华大学 | Postgraduate employment recommended method based on depth confidence network |
| CN113869010A (en) * | 2021-09-28 | 2021-12-31 | 中通服创立信息科技有限责任公司 | High-association intelligent service recommendation method |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8527510B2 (en) * | 2005-05-23 | 2013-09-03 | Monster Worldwide, Inc. | Intelligent job matching system and method |
| CN102236716A (en) * | 2011-07-12 | 2011-11-09 | 上海简胜企业管理咨询有限公司 | System for matching job hunters with vacant positions and matching method thereof |
| US9258583B2 (en) * | 2013-07-18 | 2016-02-09 | Comcast Cable Communications, Llc | Content rating |
| CN104050532A (en) * | 2014-06-19 | 2014-09-17 | 高海逵 | Resume generating method and resume generating system |
| CN104933239A (en) * | 2015-06-09 | 2015-09-23 | 江苏大学 | Hybrid model based personalized position information recommendation system and realization method therefor |
| CN105159962B (en) * | 2015-08-21 | 2018-08-17 | 北京全聘致远科技有限公司 | Position recommends method and apparatus, resume to recommend method and apparatus, recruitment platform |
| CN105512864A (en) * | 2016-01-28 | 2016-04-20 | 丁沂 | Method for automatically acquiring post professional ability requirements based on internet |
| CN105574788A (en) * | 2016-02-05 | 2016-05-11 | 北京普猎创新网络科技有限公司 | Competency label-based training providing method |
| CN105975609A (en) * | 2016-05-18 | 2016-09-28 | 德稻全球创新网络（北京）有限公司 | Industrial design product intelligent recommendation method and system |
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