CN109165295A - A kind of intelligence resume appraisal procedure - Google Patents
A kind of intelligence resume appraisal procedure Download PDFInfo
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- CN109165295A CN109165295A CN201811131459.XA CN201811131459A CN109165295A CN 109165295 A CN109165295 A CN 109165295A CN 201811131459 A CN201811131459 A CN 201811131459A CN 109165295 A CN109165295 A CN 109165295A
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- 230000007115 recruitment Effects 0.000 claims abstract description 52
- 238000012216 screening Methods 0.000 claims abstract description 12
- 230000014509 gene expression Effects 0.000 claims description 13
- 239000000284 extract Substances 0.000 claims description 12
- 239000003550 marker Substances 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 3
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Abstract
The invention discloses a kind of intelligent resume appraisal procedures, comprising: recruitment data acquisition system is obtained from database, the recruitment data acquisition system includes at least enterprises recruitment information；Data are extracted from the recruitment data acquisition system, the data include: that one or more attributes corresponding recruitment requirement, attribute in position are in enterprises recruitment information for characterizing the parameter of job requirement；Obtain resume text data one by one from database；Data are extracted from the resume text data, wherein the data packet includes: one or more is for characterizing the attribute of applicant's feature；It will be matched by the data extracted in resume text data with the data by being extracted in recruitment data acquisition system, the data write-in database fitted through, the present invention solves artificial screening resume in the prior art, and time-consuming, low efficiency, and screens the source and comprehensive to data by information approach and require excessively high the problem of causing limitation.
Description
Technical field
The present invention relates to technical field of data processing more particularly to a kind of intelligent resume appraisal procedures.
Background technique
The resume that current many enterprise HR deliver applicant toward contact by the way of manual identified, judgement, screening,
This mode more relies on the micro-judgment of individual, and in prolonged screening, assessment, evaluator is easy to browse phase to repetition
As content feel fatigue, to influence engagement efficiency and subjective judgement, on the other hand, in existing recruitment, enterprise
The characteristics of industry also tends to find the talent by recruitment website, most of such recruitment websites is through social networks, behavior
Data etc. portray applicant comprehensively, carry out comprehensive assessment to the interest, personality, ability of applicant, enterprise is helped to look for
To the suitable talent, but itself the problem is that: for assess needed for data demand it is higher, accuracy limit to larger, difficulty
It is higher, not yet occur effective solution at present.
Summary of the invention
Mirror is with this, and the purpose of the present invention is to provide a kind of intelligent resume appraisal procedures, at least to solve problem above.
A kind of intelligence resume appraisal procedure, comprising:
Recruitment data acquisition system is obtained from database, the recruitment data acquisition system includes at least enterprises recruitment information；
Data are extracted from the recruitment data acquisition system, wherein the data packet includes: one or more attributes are in position
Corresponding recruitment requirement, the attribute are in enterprises recruitment information for characterizing the parameter of job requirement；
Obtain resume text data one by one from database；
Data are extracted from the resume text data, wherein the data packet includes: one or more is for characterizing application
The attribute of person's feature；
It will be matched, matched with the data by being extracted in recruitment data acquisition system by the data extracted in resume text data
By resume text data be written database.
Further, described to obtain resume text data one by one from database, including to the resume text data into
Row screening, the screening includes: to remove ineligible resume text from the resume text data；Sieve is obtained one by one
Resume text data after choosing.
Further, the ineligible resume text, for the resume text for not using semi-structured data form.
Further, data are extracted from the resume text data, comprising:
It is essential information class and complex information class set by resume text dividing；
Data are extracted from essential information class；
Classify to complex information class set；
Target information is extracted from complex information class.
Further, when being essential information class and complex information class set by resume text dividing, first using based on just
Then the matching strategy of expression formula identifies to find cut-off keyword；If without identifiable keyword, by resume text
This preceding 5-10 this conduct of composing a piece of writing obscures basic info class to extract data.
Further, data are extracted from essential information class, comprising:
Strong marker element content is identified；
Element type is judged based on element contextual location.
Further, when classifying to complex information class set, it is taken based on the key character of regular expression first
Matching strategy classifies to complex information class set；If can not find the keyword to match, by analysis text format,
Font carries out the classification of complex information class set, or is classified by the Algorithms for Automatic Classification based on simple vector.
Further, it is matched when extracting target information from complex information class using the key character based on regular expression
Strategy extracts target information, and the target information is in resume text data for characterizing applicant's professional skill and technical level
Information.
Compared with prior art, the beneficial effects of the present invention are:
A kind of intelligent resume appraisal procedure provided by the invention, by being carried out respectively to recruitment information and resume text data
Specific information extracts and Auto-matching, the process of screening resume is simplified, compared to traditional artificial screening resume mode, efficiency
It is higher, reduce the use to human resources, it is on the other hand, lower for the source requirement of garbled data, from the letter of deliverer
Required data can be extracted in going through automatically, according to that can adjust according to the demand of recruitment side, target information extracts accuracy rate more for screening
It is high.
Detailed description of the invention
To describe the technical solutions in the embodiments of the present invention more clearly, make required in being described below to embodiment
Attached drawing is briefly described, it should be apparent that, the accompanying drawings in the following description is only the preferred embodiment of the present invention, for
For those of ordinary skill in the art, without creative efforts, it can also be obtained according to these attached drawings other
Attached drawing.
Fig. 1 is the intelligent resume appraisal procedure flow diagram of the embodiment of the present invention.
Fig. 2 is that the resume text data of the embodiment of the present invention extracts flow diagram.
Specific embodiment
The principle and features of the present invention will be described below with reference to the accompanying drawings, and cited embodiment is served only for explaining this hair
It is bright, it is not intended to limit the scope of the present invention.
Embodiment below can be applied in common terminal, such as computer.Certain reality below
Applying example also can be applied in server, and server is it also will be understood that be the equipment being made of one or more computers.Cause
This, the structure of computer illustrated below is also applied for server.When mobile terminal computing capability gradually enhances, implement below
Example can also be implemented in the terminal.Certainly, the step in following embodiments or module can be respectively in different clothes
Business device or terminal perhaps carry out carrying out necessary number between these servers or terminal or mobile terminal in mobile terminal
According to interaction.
Referring to Fig.1, the present invention provides a kind of intelligent resume appraisal procedure, specifically includes:
Step S1, obtains recruitment data acquisition system from database, and the recruitment data acquisition system is believed including at least enterprises recruitment
Breath.
In above-mentioned steps, as an alternative embodiment, the recruitment data acquisition system stored in database is recruitment
The enterprises recruitment information of enterprise's the last time, since the recruitment standard of recruitment enterprise may change over time,
Requirement for applicant can generate variation, therefore, will recruit the enterprises recruitment information of enterprise's the last time as recruitment data
The source of set, to guarantee the accuracy of recruitment target.
Step S2 extracts data from the recruitment data acquisition system, wherein the data packet includes: one or more attributes exist
Corresponding recruitment requirement, the attribute are in enterprises recruitment information for characterizing the parameter of job requirement in position.
In above-mentioned steps, the attribute for characterizing job requirement can be educational background required by position, profession, skill
The parameters such as energy, working experience.The data of the extraction are then the specific requirements to the attribute, for example, in enterprises recruitment information
It is required that applicant's educational background of position should be master or more, profession should be soft project.
Step S3 obtains resume text data one by one from database；
In above-mentioned steps, resume text that the resume text data is delivered by applicant.In implementation of the invention
In example, above-mentioned steps, which further comprise, screens the resume text data, and the screening includes: by ineligible letter
Text is gone through to remove from the resume text data；The resume text data after screening is obtained one by one.It is described ineligible
Resume text, for the resume text for not using semi-structured data form.
Text data can be divided into three classes by the characteristics of according to text: structural data is strictly given birth to according to certain format
At text data, such as various bills, school report etc.；Without structured data, i.e., with the mankind be accustomed to exchange way be dominate,
In accordance with text data of natural syntax rule, such as news report, novel, prose etc.；Semi-structured data, the text of this form
Notebook data is between the above two, and in terms of the entirety of text, this kind of text data has certain format constraints, not in full conformity with certainly
Right syntax rule, but from part, and natural syntax rule tissue language has been used, such as notify, announce, is most of
Resume etc. belongs to the text of semi-structured form.Machine is to the identification of resume text data and the pumping of information for ease of calculation
It takes, therefore needs that the resume of semi-structured data form will not be used wherein when obtaining the resume text data that applicant delivers
Text removal removes the text for not using conventional resume to write form.
Step S4 extracts data from the resume text data, wherein the data packet includes: one or more is used for table
Levy the attribute of applicant's feature.
It is described for characterizing the attribute of applicant's feature in above-mentioned steps, it can be name, gender, school, educational background, specially
The information such as industry, technical ability, working experience.
Step S5, by the data by being extracted in resume text data and the data progress by being extracted in recruitment data acquisition system
Match, the data write-in database fitted through.
In step S5, by will by extracted in resume text data characterization applicant's feature data with by recruitment data
The data for the characterization recruitment enterprises recruitment requirement extracted in set are matched, and fitting through indicates that certain aspect of applicant is special
Sign meets the recruitment requirement of recruitment enterprise, then the resume text data fitted through is written in database, facilitates human resources
Department arranges applicant to interview according to the resume text data in database, improves recruitment work efficiency.
In step S4, data are extracted from the resume text data on the basis of the above embodiments referring to Fig. 2, are wrapped
It includes:
Resume text dividing is essential information class and complex information class set by step S41；
Step S42 extracts data from essential information class；
Step S43 classifies to complex information class set；
Step S44 extracts target information from complex information class.
In an embodiment of the present invention, resume text is divided into essential information class and complex information class, it is special from the content of class
It is seen on point, essential information class refers to the classification being made of the essential information of applicant, and classification herein has a certain common trait
Text.Essential information class characterizes the basic condition of applicant, wherein may include multiple essential information items, such as name,
Date of birth, school, educational background, profession, native place, contact method etc..Between being generally with space, carriage return character etc. between essential information item
Every.Complex information class refers to that the classification being made of the complex information of applicant, complex information class characterize the spread scenarios of applicant
Information, and might have multiple complex information classes in resume text, for example, education experience, work experience, project undergo,
Training experience etc., these complex information classes then constitute complex information class set.
Between essential information class and complex information class, complex information class generally have apparent segmentation mark, example between each other
Such as keyword, font, format, it is different with content of all categories.It by resume text dividing is basic in step S41
When info class and complex information class set, as a kind of optional embodiment, the keyword based on regular expression is used first
Matching strategy is accorded with, the segmentation mark of cutting is found out, has headed feature based on text informations all kinds of in resume text, can first adopt
The title and its generic that are likely to occur in resume text are stored in key word library with the method for exhaustion, redesign regular expression
The text to match is retrieved from text, is identified as segmentation and is carried out cutting.If corresponding key character is not detected in text,
Then it is located at the beginning of resume according to the essential information of applicant in general resume text, the preceding 5-10 of resume text is composed a piece of writing
This conduct obscures basic info class to extract data, it is of course also possible to which flexible setting obscures basic info class according to actual needs
Range.
In step S42, from information required for recruitment enterprise is extracted in essential information class, specifically include:
Strong marker element content is identified；
Element type is judged based on element contextual location.
Essential information class is made of several essential information items, and essential information item generally comprises a title element and one
" name " in content element, such as resume text is title element, and " Zhang San " after " name " is content element, from resume text
The power of this content identification sees, title element this kind from its content of text be can determine whether its classification belong to strong mark
Element.By design regular expression, the strong marker element in resume text is retrieved, it then, can be according to the upper of element
Hereafter position judges the type of element.For example, in essential information class, if among two strong marker element being a weak mark
Know element or without marker element, then it is assumed that a weak marker element is the corresponding content member of previous element without marker element
Element.After identifying the element type in essential information class, therefrom taken out further according to key character matching strategy design regular expression
Take out information needed.
In step S43, due to typically including multiple complex information classes, such as education background, work warp in resume text
It goes through, skill technique, hobby, social practice etc., these complex information classes constitute complex information class set, therefore,
Complete to the cutting of essential information class in resume text and complex information class set after, need to carry out complex information class set into
The classification of one step.The key character matching strategy for being taken based on regular expression first classifies to complex information class set, absolutely
Most of resume texts are designed with the keyword of education background, work experience one kind, thus make in this way to complex information
Class progress classification speed is fast, accuracy rate is high, good classification effect.If can not find the keyword to match, according to complex information class
Title the characteristics of generalling use different fonts, size and format from content, pass through the format of analysis text, font carries out
The classification of complex information class set, or classified by the Algorithms for Automatic Classification based on simple vector.
The principle of classification of Algorithms for Automatic Classification based on simple vector is: being that every class text collection generates one according to arithmetic average
A center vector comes then, to determine new text vector in new text, and calculates new text vector and every class text collection center vector
Distance, i.e. similarity, the stylish text that finally determines to classify belongs to text apart from nearest class.
In step S44, after completing to the classification of complex information class, the strategy based on keyword match designs regular expressions
Formula extracts target information, and the target information is in resume text data for characterizing applicant's professional skill and technical level
Information, above- mentioned information will be extracted the information progress of the characterization job requirement to extract in the recruitment information with recruitment enterprise
Match, when matching, requires applicant that need to have Senior Software Engineer's occupation according to job requirement information, such as in recruitment information and recognize
Card, then design regular expression, screen to the target information by extracting in complex information class, accordingly if retrieving corresponding letter
Otherwise the resume text is then considered as into database and is unsatisfactory for job requirement by breath by resume text storage.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (8)
1. a kind of intelligence resume appraisal procedure characterized by comprising
Recruitment data acquisition system is obtained from database, the recruitment data acquisition system includes at least enterprises recruitment information；
Data are extracted from the recruitment data acquisition system, wherein the data packet includes: one or more attributes are corresponding in position
Recruitment requirement, the attribute is in enterprises recruitment information for characterizing the parameter of job requirement；
Obtain resume text data one by one from database；
Data are extracted from the resume text data, wherein the data packet includes: one or more is for characterizing applicant spy
The attribute of sign；
It will be matched, fitted through with by the data extracted in recruitment data acquisition system by the data extracted in resume text data
Resume text data be written database.
2. a kind of intelligent resume appraisal procedure according to claim 1, which is characterized in that described to be obtained one by one from database
Resume text data is taken, including the resume text data is screened, the screening includes: by ineligible resume
Text is removed from the resume text data；The resume text data after screening is obtained one by one.
3. a kind of intelligent resume appraisal procedure according to claim 2, which is characterized in that the ineligible resume
Text, for the resume text for not using semi-structured data form.
4. a kind of intelligent resume appraisal procedure according to claim 1, which is characterized in that from the resume text data
Extract data, comprising:
It is essential information class and complex information class set by resume text dividing；
Data are extracted from essential information class；
Classify to complex information class set；
Target information is extracted from complex information class.
5. a kind of intelligent resume appraisal procedure according to claim 4, which is characterized in that by resume text dividing be basic
When info class and complex information class set, the matching strategy based on regular expression is used to identify to seek keyword first
Look for cut-off；If the preceding 5-10 of resume text this conduct of composing a piece of writing is obscured basic info class to take out without identifiable keyword
Access evidence.
6. a kind of intelligent resume appraisal procedure according to claim 4, which is characterized in that extract number from essential information class
According to, comprising:
Strong marker element content is identified；
Element type is judged based on element contextual location.
7. a kind of intelligent resume appraisal procedure according to claim 4, which is characterized in that carried out to complex information class set
When classification, the key character matching strategy for being taken based on regular expression first classifies to complex information class set；If looking for
Less than the keyword to match, then the classification of complex information class set is carried out by the format of analysis text, font, or pass through base
Classify in the Algorithms for Automatic Classification of simple vector.
8. a kind of intelligent resume appraisal procedure according to claim 4, which is characterized in that extract mesh from complex information class
Target information is extracted using the key character matching strategy based on regular expression when marking information, the target information is resume text
For characterizing the information of applicant's professional skill and technical level in notebook data.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110263148A (en) * | 2019-06-27 | 2019-09-20 | 中国工商银行股份有限公司 | Intelligent resume selection method and device |
| CN111598462A (en) * | 2020-05-19 | 2020-08-28 | 厦门大学 | Resume screening method for campus recruitment |
| CN112256877A (en) * | 2019-12-30 | 2021-01-22 | 北京来也网络科技有限公司 | Resume screening method, device, equipment and storage medium combining RPA and AI |
| CN114219456A (en) * | 2021-12-28 | 2022-03-22 | 珠海聘仓未来科技有限公司 | Human resource resume management system and method |
| CN114444489A (en) * | 2022-01-29 | 2022-05-06 | 北京金山数字娱乐科技有限公司 | Information extraction method and device and electronic equipment |
| CN117993876A (en) * | 2024-04-03 | 2024-05-07 | 四川蓉城蕾茗科技有限公司 | Resume evaluation system, method, device and medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104599031A (en) * | 2014-11-06 | 2015-05-06 | 河南智业科技发展有限公司 | Resume model matching system and method |
| CN105117863A (en) * | 2015-09-28 | 2015-12-02 | 北京橙鑫数据科技有限公司 | Resume position matching method and device |
| CN105183742A (en) * | 2015-06-12 | 2015-12-23 | 南京富士通南大软件技术有限公司 | Resume identification method |
| CN107590133A (en) * | 2017-10-24 | 2018-01-16 | 武汉理工大学 | The method and system that position vacant based on semanteme matches with job seeker resume |
| CN107729532A (en) * | 2017-10-30 | 2018-02-23 | 北京拉勾科技有限公司 | A kind of resume matching process and computing device |
| CN107808016A (en) * | 2017-11-29 | 2018-03-16 | 四川九鼎智远知识产权运营有限公司 | A kind of online resume matching process |
| CN107862079A (en) * | 2017-11-29 | 2018-03-30 | 四川九鼎智远知识产权运营有限公司 | A kind of online resume Matching Platform |
-
2018
- 2018-09-27 CN CN201811131459.XA patent/CN109165295B/en not_active Expired - Fee Related
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104599031A (en) * | 2014-11-06 | 2015-05-06 | 河南智业科技发展有限公司 | Resume model matching system and method |
| CN105183742A (en) * | 2015-06-12 | 2015-12-23 | 南京富士通南大软件技术有限公司 | Resume identification method |
| CN105117863A (en) * | 2015-09-28 | 2015-12-02 | 北京橙鑫数据科技有限公司 | Resume position matching method and device |
| CN107590133A (en) * | 2017-10-24 | 2018-01-16 | 武汉理工大学 | The method and system that position vacant based on semanteme matches with job seeker resume |
| CN107729532A (en) * | 2017-10-30 | 2018-02-23 | 北京拉勾科技有限公司 | A kind of resume matching process and computing device |
| CN107808016A (en) * | 2017-11-29 | 2018-03-16 | 四川九鼎智远知识产权运营有限公司 | A kind of online resume matching process |
| CN107862079A (en) * | 2017-11-29 | 2018-03-30 | 四川九鼎智远知识产权运营有限公司 | A kind of online resume Matching Platform |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110263148A (en) * | 2019-06-27 | 2019-09-20 | 中国工商银行股份有限公司 | Intelligent resume selection method and device |
| CN112256877A (en) * | 2019-12-30 | 2021-01-22 | 北京来也网络科技有限公司 | Resume screening method, device, equipment and storage medium combining RPA and AI |
| CN111598462A (en) * | 2020-05-19 | 2020-08-28 | 厦门大学 | Resume screening method for campus recruitment |
| CN111598462B (en) * | 2020-05-19 | 2022-07-12 | 厦门大学 | Resume screening method for campus recruitment |
| CN114219456A (en) * | 2021-12-28 | 2022-03-22 | 珠海聘仓未来科技有限公司 | Human resource resume management system and method |
| CN114444489A (en) * | 2022-01-29 | 2022-05-06 | 北京金山数字娱乐科技有限公司 | Information extraction method and device and electronic equipment |
| CN114444489B (en) * | 2022-01-29 | 2024-07-02 | 北京金山数字娱乐科技有限公司 | Information extraction method and device and electronic equipment |
| CN117993876A (en) * | 2024-04-03 | 2024-05-07 | 四川蓉城蕾茗科技有限公司 | Resume evaluation system, method, device and medium |
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