CN105512864A - Method for automatically acquiring post professional ability requirements based on internet - Google Patents
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Abstract
The invention discloses a method for automatically acquiring post professional ability requirements based on internet, which acquires recruiting information from recruiting websites through an automatic mode, stores the recruiting information into a local database, extracts the recruiting information aiming to a specific job, and automatically extracts professional ability requirements of the specific job by utilizing natural language processing technology and data mining technology. Compared with a traditional method, the method for automatically acquiring post professional ability requirements based on the internet has the advantages that 1 the method for automatically acquiring post professional ability requirements based on the internet is an automatic process, and is rapid in time, high in efficiency and low in cost; and 2 the method for automatically acquiring post professional ability requirements based on the internet is large in acquired data samples, updates data in time, and has representativeness in analysis results.
Description
Technical field
The present invention relates to internet and technical field of data processing, particularly relate to a kind of automatic obtaining method of the Positional Competency demand based on internet.
Background technology
Make full use of Information Technology Methods, promote the Occupational key ability of vocational education student; Relying on internet medium capability, enterprise practical demand and vocational education are cultivated and fully combine, is that China catches up with and even surmounts the unique feasible selection of vocational education advanced country.Current, internet especially recruitment website has a large amount of recruitment information, in these recruitment informations, enterprise has explicitly pointed out the vocational ability demand in concrete post, these recruitment informations can with helping Students ' Employment, the Positional Competency demand obtained can be used for optimizing Talents Cultivation and course teaching, for the education sector functional department that is correlated with carries out science decision and provides Data support.
But the mode nowadays obtaining relevant station vocational ability demand is mainly by survey, interview and utilize network to carry out manual retrieval to obtain data, then the data obtained are arranged and analyzed, the data volume that this method gathers usually is little, collection face is narrow, data can not upgrade in time, and the result of therefore last statistical study does not often possess representativeness.
Summary of the invention
In order to overcome the deficiencies in the prior art, the invention provides a kind of automatic obtaining method of the Positional Competency demand based on internet, this method obtains recruitment information by the mode of robotization from recruitment website, and be kept in local data bank, for a certain concrete post, utilize the recruitment information in this post a large amount of, by natural language processing technique and data mining technology, automatically extract the vocational ability demand in this post.
The present invention for solving the problems of the technologies described above adopted technical scheme is:
Based on an automatic obtaining method for the Positional Competency demand of internet, the method comprises the following steps:
Step 1, utilizes crawler technology to crawl recruitment information on recruitment website, and is preserved in a database by recruitment information;
Step 2, position title and the job position request data of a certain class position are retrieved from database, and in the result returned, retrieve position title and the job position request data in a certain concrete post, the result of twice retrieval is kept at respectively in position text and concrete post text;
Step 3, the interface utilizing Words partition system to provide carries out participle to the position text described in step 2 and concrete post text respectively, builds the word vector space of two texts; The element of described word vector space is the word comprised in position text or concrete post text.
Step 4, scans every bar recruitment information in two texts, in conjunction with respective word vector space, adds up number of times that these words occur in every bar information respectively thus builds " recruitment information-word " frequency matrix; Add up each word probability of occurrence in matrix corresponding to concrete post text and position text respectively;
Step 5, the word in the text of concrete post is screened and the vocational skills be combined to form required by this post according to the word probability obtained in step 4, be specially and threshold value is set, if the probability that word occurs in the text of concrete post deducts the probability that this word occurs in position text be greater than threshold value, then by the vocational skills keyword of this word definitions required by this concrete post; In the text of concrete post, all words meeting above-mentioned condition form the vocational skills required by this post jointly.
As preferably, the recruitment information that crawls described in step 1 specifically comprises the following steps:
Step 101, obtains and resolves the recruitment website employment searches page and obtain all functions in this website, industry and area name and reference numeral, preserves in the local database;
Step 102, utilizes function, the numbering of industry and area name and correspondence is combined into search keyword, utilize the inner search engine of this website, obtain the information list comprising recruitment information hyperlink;
Step 103, resolves information list by circulation, obtains complete recruitment information and position name and preserves in a database.Also comprise in this step and utilize database script to carry out duplicate removal and optimization to the hyperlink data repeating to crawl.
As preferably, described step 1 also comprises carries out mark to the webpage crawled and prevents from repeating to crawl acquired data in the hyperlinked information of database, facilitates Data Update and analysis.
As preferably, in " recruitment information-word " described in step 4 frequency matrix, every a line represents a recruitment information, each row represents a word, or each row represents a recruitment information, every a line represents a word, and corresponding matrix element is the frequency of occurrence of word in this recruitment information.The described frequency is the weighting frequency, namely according to different vocabulary for job position request significance level difference different weights are set.Such as: if having prefix word " to be proficient in " before certain word arranging weights is 2; " to be familiar with " and " skillfully " to arrange weights be 1.6; " grasp " arranges weights is 1.5, and other arrange weights is 1.
Compared with prior art, the invention has the beneficial effects as follows:
1, this method is the process of a robotization, and the time is fast, and efficiency is high, and cost is low.
2, the data sample obtained is large, and data upgrade in time, and analysis result is representative.
Accompanying drawing explanation
Fig. 1 is the inventive method process flow diagram.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described.
Based on an automatic obtaining method for the Positional Competency demand of internet, comprise the following steps:
Step 1, utilizes crawler technology to crawl recruitment information on recruitment website, and is preserved in a database by recruitment information;
The recruitment information that crawls described in step 1 specifically comprises the following steps:
Step 101, obtains and resolves the recruitment website employment searches page and obtain all functions in this website, industry and area name and reference numeral, preserves in the local database;
Step 102, utilizes function, the numbering of industry and area name and correspondence is combined into search keyword, utilize the inner search engine of this website, obtain the information list comprising recruitment information hyperlink;
Step 103, resolves information list by circulation, obtains complete recruitment information and position name and preserves in a database.Also comprise in this step and utilize database script to carry out duplicate removal and optimization to the hyperlink data repeating to crawl.
Step 2, position title and the job position request data of a certain class position (as: software engineer) are retrieved from database, and in the result returned, retrieve position title and the job position request data in a certain concrete post (as: java Developmental Engineer), the result of twice retrieval is kept in different texts respectively.Post title in text in each recruitment information and job position request with tab-delimited, and separate (should ensure not comprise this special symbol in recruitment information) with a special symbol between every bar recruitment information.
Step 3, read this two texts respectively, the interface utilizing Words partition system of increasing income to provide carries out participle to these two texts, then remove monocase and repeated word, build the word vector space (that is: these two texts which different word are made up of) of two texts respectively.
Step 4, to line by line scan every bar information (i.e. post) in latter two text of participle, in conjunction with respective word vector space, add up number of times that these words occur in every bar information respectively thus build recruitment information (post)-word matrix, in matrix, every a line represents a recruitment information (post), each row represents a word, corresponding matrix element is set to the weighting frequency of occurrence of word in this information (post), and concrete technical scheme is: if having prefix word " to be proficient in " before certain word arranging weights is 2; " to be familiar with " and " skillfully " to arrange weights be 1.6; " grasp " arranges weights is 1.5, and other arrange weights is 1.
Add up each word accumulated weights frequency of occurrences in the matrix corresponding to the text of concrete post, specific formula for calculation is: the accumulated weights frequency of occurrence sum occurred in the recruitment information that the accumulated weights frequency of occurrence occurred in the recruitment information that word comprises at this text comprises at this text divided by all words.
Add up the accumulated weights frequency of occurrences of these words in the matrix corresponding to a certain class position text.
Step 5, a threshold value (5%-10%) is set, if word accumulated weights frequency of occurrences in the text of concrete post deducts this word accumulated weights frequency of occurrences in a certain class position text be greater than this threshold value, so this word is exactly these vocational skills required by concrete post, and all words meeting this condition constitute the vocational skills required by this post jointly.
The part do not set forth in instructions is prior art or common practise.The present embodiment only for illustration of this invention, and is not used in and limits the scope of the invention, and the amendment such as the equivalent replacement that those skilled in the art make for the present invention is all thought to fall in this invention claims institute protection domain.
Claims (8)
1., based on an automatic obtaining method for the Positional Competency demand of internet, it is characterized in that: the method comprises the following steps:
Step 1, utilizes crawler technology to crawl recruitment information on recruitment website, and is preserved in a database by recruitment information;
Step 2, position title and the job position request data of a certain class position are retrieved from database, and in the result returned, retrieve position title and the job position request data in a certain concrete post, the result of twice retrieval is kept at respectively in position text and concrete post text;
Step 3, the interface utilizing Words partition system to provide carries out participle to the position text described in step 2 and concrete post text respectively, builds the word vector space of two texts;
Step 4, scans every bar recruitment information in two texts, in conjunction with respective word vector space, adds up number of times that these words occur in every bar information respectively thus builds " recruitment information-word " frequency matrix; Add up each word probability of occurrence in matrix corresponding to concrete post text and position text respectively;
Step 5, screens the word in the text of concrete post and the vocational skills be combined to form required by this post according to the word probability obtained in step 4.
2. the automatic obtaining method of a kind of Positional Competency demand based on internet according to claim 1,
It is characterized in that: the recruitment information that crawls described in step 1 specifically comprises the following steps:
Step 101, obtains and resolves the recruitment website employment searches page and obtain all functions in this website, industry and area name and reference numeral, preserves in the local database;
Step 102, utilizes function, the numbering of industry and area name and correspondence is combined into search keyword, utilize the inner search engine of this website, obtain the information list comprising recruitment information hyperlink;
Step 103, resolves information list by circulation, obtains complete recruitment information and position name and preserves in a database.
3. the automatic obtaining method of a kind of Positional Competency demand based on internet according to claim 2, is characterized in that: step 103 comprises and utilizes database script to carry out duplicate removal and optimization to the hyperlink data repeating to crawl.
4. the automatic obtaining method of a kind of Positional Competency demand based on internet according to claim 1 and 2, it is characterized in that: described step 1 also comprises carries out mark to the webpage crawled and prevent from repeating to crawl acquired data in the hyperlinked information of database, facilitates Data Update and analysis.
5. the automatic obtaining method of a kind of Positional Competency demand based on internet according to claim 1, is characterized in that: the element of the word vector space described in step 3 is the word comprised in position text or concrete post text.
6. the automatic obtaining method of a kind of Positional Competency demand based on internet according to claim 1, it is characterized in that: in " recruitment information-word " described in step 4 frequency matrix, every a line represents a recruitment information, each row represents a word, or each row represents a recruitment information, every a line represents a word, and corresponding matrix element is the frequency of occurrence of word in this recruitment information.
7. the automatic obtaining method of a kind of Positional Competency demand based on internet according to claim 6, is characterized in that: the described frequency is the weighting frequency, namely according to different vocabulary for job position request significance level difference different weights are set.
8. the automatic obtaining method of a kind of Positional Competency demand based on internet according to claim 1, it is characterized in that: in step 5, the concrete grammar of screening is: arrange threshold value, if the probability that word occurs in the text of concrete post deducts the probability that this word occurs in position text be greater than threshold value, then by the vocational skills keyword of this word definitions required by this concrete post; In the text of concrete post, all words meeting above-mentioned condition form the vocational skills required by this post jointly.
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Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105868968A (en) * | 2016-04-21 | 2016-08-17 | 广州爱拼信息科技有限公司 | Recruitment information analysis system and method based on machine learning |
| CN106600213A (en) * | 2016-11-15 | 2017-04-26 | 广东家易科技有限公司 | Intelligent resume management system and method |
| CN107194617A (en) * | 2017-07-06 | 2017-09-22 | 北京航空航天大学 | A kind of app software engineers soft skill categorizing system and method |
| CN107506389A (en) * | 2017-07-27 | 2017-12-22 | 北京德塔精要信息技术有限公司 | A kind of method and apparatus for extracting position skill requirement |
| CN107885725A (en) * | 2017-11-06 | 2018-04-06 | 山东浪潮云服务信息科技有限公司 | A kind of method and device for handling recruitment data |
| CN107943881A (en) * | 2017-11-15 | 2018-04-20 | 上海壹账通金融科技有限公司 | Test database generation method, server and computer-readable recording medium |
| CN108280583A (en) * | 2018-01-26 | 2018-07-13 | 重庆工商大学 | Post skill requirement analysis method based on big data |
| CN108460699A (en) * | 2017-12-20 | 2018-08-28 | 卓智网络科技有限公司 | Teaching programme optimization method and device |
| CN108520334A (en) * | 2018-03-15 | 2018-09-11 | 考拉征信服务有限公司 | A kind of occupation reference method and apparatus |
| CN108614890A (en) * | 2018-05-04 | 2018-10-02 | 长沙麦都网络科技有限公司 | Public examination radar system |
| CN108648120A (en) * | 2018-05-11 | 2018-10-12 | 重庆工商职业学院 | A kind of institute's employment data analysis method and system |
| CN109033269A (en) * | 2018-07-10 | 2018-12-18 | 卓源信息科技股份有限公司 | A kind of Distributed Area talent supply and demand subject data crawling method |
| CN110390514A (en) * | 2019-07-26 | 2019-10-29 | 北京博海迪信息科技有限公司 | A kind of method and system based on talents market's processing talent's model information |
| CN110619506A (en) * | 2019-08-13 | 2019-12-27 | 平安科技（深圳）有限公司 | Post portrait generation method, post portrait generation device and electronic equipment |
| CN111210124A (en) * | 2019-12-26 | 2020-05-29 | 杭州威佩网络科技有限公司 | Recruitment information processing method and device |
| CN112613839A (en) * | 2020-12-25 | 2021-04-06 | 大连工业大学 | Public employment guidance method and system |
| CN112861530A (en) * | 2021-03-17 | 2021-05-28 | 华南农业大学 | Course setting analysis method based on text mining |
| CN116523225A (en) * | 2023-04-18 | 2023-08-01 | 泸州职业技术学院 | Data mining-based overturning classroom hybrid teaching method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105868968A (en) * | 2016-04-21 | 2016-08-17 | 广州爱拼信息科技有限公司 | Recruitment information analysis system and method based on machine learning |
| CN106600213A (en) * | 2016-11-15 | 2017-04-26 | 广东家易科技有限公司 | Intelligent resume management system and method |
| CN107194617A (en) * | 2017-07-06 | 2017-09-22 | 北京航空航天大学 | A kind of app software engineers soft skill categorizing system and method |
| CN107506389B (en) * | 2017-07-27 | 2020-05-19 | 北京德塔精要信息技术有限公司 | Method and device for extracting job skill requirements |
| CN107506389A (en) * | 2017-07-27 | 2017-12-22 | 北京德塔精要信息技术有限公司 | A kind of method and apparatus for extracting position skill requirement |
| CN107885725A (en) * | 2017-11-06 | 2018-04-06 | 山东浪潮云服务信息科技有限公司 | A kind of method and device for handling recruitment data |
| CN107943881A (en) * | 2017-11-15 | 2018-04-20 | 上海壹账通金融科技有限公司 | Test database generation method, server and computer-readable recording medium |
| CN108460699A (en) * | 2017-12-20 | 2018-08-28 | 卓智网络科技有限公司 | Teaching programme optimization method and device |
| CN108280583A (en) * | 2018-01-26 | 2018-07-13 | 重庆工商大学 | Post skill requirement analysis method based on big data |
| CN108520334A (en) * | 2018-03-15 | 2018-09-11 | 考拉征信服务有限公司 | A kind of occupation reference method and apparatus |
| CN108614890A (en) * | 2018-05-04 | 2018-10-02 | 长沙麦都网络科技有限公司 | Public examination radar system |
| CN108648120A (en) * | 2018-05-11 | 2018-10-12 | 重庆工商职业学院 | A kind of institute's employment data analysis method and system |
| CN108648120B (en) * | 2018-05-11 | 2021-07-09 | 重庆工商职业学院 | Academic employment data analysis method and system |
| CN109033269A (en) * | 2018-07-10 | 2018-12-18 | 卓源信息科技股份有限公司 | A kind of Distributed Area talent supply and demand subject data crawling method |
| CN110390514A (en) * | 2019-07-26 | 2019-10-29 | 北京博海迪信息科技有限公司 | A kind of method and system based on talents market's processing talent's model information |
| CN110390514B (en) * | 2019-07-26 | 2023-03-14 | 北京博海迪信息科技有限公司 | Method and system for processing talent model information based on talent market |
| CN110619506A (en) * | 2019-08-13 | 2019-12-27 | 平安科技（深圳）有限公司 | Post portrait generation method, post portrait generation device and electronic equipment |
| CN110619506B (en) * | 2019-08-13 | 2023-05-26 | 平安科技（深圳）有限公司 | Post image generation method, post image generation device and electronic equipment |
| CN111210124A (en) * | 2019-12-26 | 2020-05-29 | 杭州威佩网络科技有限公司 | Recruitment information processing method and device |
| CN112613839A (en) * | 2020-12-25 | 2021-04-06 | 大连工业大学 | Public employment guidance method and system |
| CN112861530A (en) * | 2021-03-17 | 2021-05-28 | 华南农业大学 | Course setting analysis method based on text mining |
| CN116523225A (en) * | 2023-04-18 | 2023-08-01 | 泸州职业技术学院 | Data mining-based overturning classroom hybrid teaching method |
| CN116523225B (en) * | 2023-04-18 | 2024-01-23 | 泸州职业技术学院 | Data mining-based overturning classroom hybrid teaching method |
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Application publication date: 20160420 |