CN107437131A - A kind of talent ability for university student crowd is assessed and the method for Postmatch - Google Patents
A kind of talent ability for university student crowd is assessed and the method for Postmatch Download PDFInfo
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Abstract
The invention discloses a kind of method of talent ability assessment and Postmatch for university student crowd, specific steps include the establishment of student side individual's quality model, the establishment of enterprises end position capability model, matching and marking algorithm and adaptive algorithm and Project Realization, student side individual quality model uses and teaches simulation practice model, position capability model includes two kinds of basic capacity models and certain capabilities model, from enterprises end position capability model, the relation that linear regression goes out between each variable；The overall architecture of Project Realization is by data acquisition, and data prepare and data application composition.The present invention has used big data matching algorithm, personal quality model and post capability model are calculated into matching degree, and draw everyone competitiveness to a specific position and application ranking using this data, with ability of self-teaching, improve the degree of accuracy, time cost has been saved, has improved efficiency, and has reached more preferable effect.
Description
Technical field
The present invention relates to recruitment technical field, and specifically a kind of talent ability for university student crowd is assessed and post
The method matched somebody with somebody.
Background technology
Human resources recruitment correlation technique in the market has a lot, and the country is mainly matched from evaluating result, also there is public affairs
Department is matched using resume parser, but is the resume for student the problem of existing human resources recruitment methods
Tend to homogeneity, its efficiency of algorithm is very poor to student crowd, and Text Mining Technology is easily cracked, and data are relatively more subjective；It is existing
The content of somebody's power resource recruitment methods learning is means, it is impossible to as the standard of talent recommendation, and the cycle is very long, and
It is actual also to have disconnection；In addition, existing human resources recruitment system be respectively provided with the information updating cycle it is long the shortcomings that, the resume of user
It is all low frequency operation to update and improve in study.
But evaluation and test can not really reflect the problem-solving ability of a people by simple question and answer, and evaluation and test can not be
Reused with one people.The useful information that traditional resume provides is limited.It is especially tight for graduate, these problems
Weight.University student does not have enough past experience data, and biographic information is except knowledge information, related data of seldom having the ability.
The content of the invention
It is an object of the invention to provide the talent ability for university student crowd of a kind of efficiency high, saving human cost
Assessment and the method for Postmatch, to solve the problems mentioned in the above background technology.
To achieve the above object, the present invention provides following technical scheme：
A kind of talent ability for university student crowd is assessed and the method for Postmatch, comprises the following steps that：
(1) establishment of student side individual quality model：The use of student side individual quality model teaches-simulation-and puts into practice model,
It is teaching for online content to teach module, and analog module is to obtain Students ' Comprehensive using analog, experience type teaching and evaluation and test
Soft or hard technical ability, put into practice the Project chance that module is supplied to students ' actual situation enterprise；The analog module include simulation tool and
Evaluating tool, analog module is by online commercial struggle simulation system from data analysis, business sensitive degree, financial affairs control, strategic decision
Dimension obtain student business technical ability evaluation, analog module by personal evaluating system from individual leadership power, ditch air grating, association
The dimension for making style obtains the personal soft skill evaluation of student；
(2) establishment of enterprises end position capability model：The position capability model includes two kinds of basic capacity models and spy
Capability model, basic capacity model include basic skill set requirements and corporate culture, and certain capabilities model includes specific post
Skill set requirements；The data of the employee of outstanding performance on existing recruitment post are gathered by enterprise HR, the collection of the data passes through
Simulation and evaluation and test are completed, while gather post performance Judgement Matrix, and the general character in these data is included into the basic capacity of company
Model, remainder data is included into post capability model；
(3) matching and marking algorithm：From enterprises end position capability model, the pass that linear regression goes out between each variable
System, marking algorithm calculate each student in the ability value of each position, and then sort proprietary score, are obtained with hundredths
With degree index, the above-mentioned algorithm of overall crowd's repetition is applied for plus all, has drawn competitiveness ranking；
(4) adaptive algorithm and Project Realization：The overall architecture of Project Realization is by data acquisition, and data prepare and data should
With composition.
As further scheme of the invention：The module of teaching includes network opening course MOOC modules, case
Module and exercise module, the data that system is grasped by exercise module collection student to knowledge point.
Compared with prior art, the beneficial effects of the invention are as follows：
The present invention has used big data matching algorithm, and personal quality model and post capability model are calculated into matching degree, and
And everyone competitiveness to a specific position and application ranking are drawn using this data, there is ability of self-teaching, energy
It is enough to be relied primarily at this stage by training and use, the raising degree of accuracy, the match selection solved between mass talent and post
The problem of HR artificial mass-elections, time cost is saved, has improved efficiency, and has reached more preferable effect.
Brief description of the drawings
Fig. 1 is data acquisition schematic diagram in the present invention.
Fig. 2 is data application schematic diagram in the present invention.
Embodiment
The technical scheme of this patent is described in more detail with reference to embodiment.
Fig. 1-2 is referred to, a kind of talent ability for university student crowd is assessed and the method for Postmatch, specific steps
It is as follows：
(1) establishment of student side individual quality model：The use of student side individual quality model teaches-simulation-and puts into practice model,
It is teaching for online content to teach module, and analog module is comprehensive using analog, experience type teaching and evaluation and test acquisition student
Soft or hard technical ability is closed, puts into practice the Project chance that module is supplied to students ' actual situation enterprise；It is described teach module and include network open
Put course MOOC modules, case module and exercise module, the data that system is grasped by exercise module collection student to knowledge point；
The analog module includes simulation tool and evaluating tool, and analog module is by online commercial struggle simulation system from data analysis, business
Industry susceptibility, financial affairs control, the dimension of strategic decision obtain the business technical ability evaluation of student, and analog module is by individual's evaluation and test
The dimension united from individual leadership power, ditch air grating, the style that cooperates obtains the personal soft skill evaluation of student；Analog module is student
The emphasis for holding personal quality model to establish.Simulation has a low-risk, zero cost, can high-frequency the characteristics of occurring, and simulation is more
Temper the integration capability of a people；Practice post, public good project and some other task that module is provided by enterprise are put into practice, is allowed
Students have the chance that practice is practiced, and these projects return the true practical data of student by putting into practice module.
(2) establishment of enterprises end position capability model：The position capability model includes two kinds of basic capacity models and spy
Capability model, basic capacity model include basic skill set requirements and corporate culture, and certain capabilities model includes specific post
Skill set requirements；The data of the employee of outstanding performance on existing recruitment post are gathered by enterprise HR, the collection of the data passes through
Simulation and evaluation and test are completed, while gather post performance Judgement Matrix, and the general character in these data is included into the basic capacity of company
Model, remainder data is included into post capability model；The classification of position capability model be conceived to and meanwhile meet help enterprise look for it is suitable
People and high potential people.For there is very strong professional skill to require that the university student in post recruits, the definition of the latent crowd of height and
Be more challenge and practical significance.
(3) matching and marking algorithm：Matching between personal quality model and position capability model is a typical probability
Statistical model problem, we are from enterprises end position capability model, the relation that linear regression goes out between each variable, and marking is calculated
Method calculates each student in the ability value of each position, and then sorted proprietary score, and matching degree index is obtained with hundredths,
The above-mentioned algorithm of overall crowd's repetition has been applied for plus all, has drawn competitiveness ranking；We use linear regression herein
The reason for be：1) computation complexity is simplified：Final judge is comparative result ranking, as long as rank order does not change,
The absolute value error matched somebody with somebody is unimportant；2) the variable quantity of capability model is more, and can often change.Linear equation can be very well
Ground adapts to this change；Competence dimension is defined first, is allowed to Observable, denumerable value, and being consistent property.These dimensions can
To be obtained from multiple means.For example simulate, evaluate and test, artificial evaluation etc..It is a linear equation that we, which define each dimension,；p
=a1X1+a2X2+...；It is a post capability model definition formula again, provides a questionnaire to HR, understand basic energy
Power requirement, the performance Judgement Matrix in some post is also obtained, help understands professional ability and required, each energy in all these questionnaires
Power is required for the numerical value marking according to 1-5, it is assumed that all dimensions are all meaningful, and simply these data of different company's weight have
Difference, it is assumed that the dimension weight that does not occur of dimension weight ratio for appearing in basic capacity or professional ability requirement has 1 quantity
Level, both 10 times of difference.So typically define score 1, score 2, score 3, score 4, the dimension of score 5, their initial weight
It is 1,10,20,30,40,50.Final a position is combined by basic capacity model and professional ability model, and two models have certainly
Oneself coefficient, form a final equation.
J=c1 basic capacity+c2 professional abilities；
Basic capacity=a1P1+a2P2+...；
Professional ability=b1P1+b2P2+...；
Once it is determined that the capability model in each post, by the paired student of these model conversions, HR is available to be pushed away marking algorithm
Recommend value, marking algorithm calculates each student in the ability value of each position, and then sort proprietary score.Score operation 90%
Student's matching degree of crowd is chosen as A, is B more than 80% crowd's matching value, and the matching value more than 70% crowd is C, more than 60%
Matching value be D, it is remaining to be poor.Equally, the above-mentioned algorithm of overall crowd's repetition has been applied for plus all in a user,
Draw competitiveness ranking.
We say that matching degree is the embodiment of absolute competitiveness.It is not that each position is attractive to owner, user
What is more taken a fancy to is if how much I applies for this position chance.Competitiveness ranking embodies data in this case.For big
Most companies, student are uncomprehending, there is information asymmetry between both sides.Competitiveness can reduce opportunity cost, band to user
Carry out ignorant job opportunity originally；Because the relationship match of not all people and position is required for being calculated, using policy network
Network and value network, the possibility for probability very little of having skimmed, amount of calculation can be declined 1 order of magnitude；Model training be algorithm into
The key of work(, and must condition.Assuming that the formula of each position is different, but also in change.Make system true
HR, the quick dynamic ability of self-teaching of algorithm requirement can just be serviced；Way is that the recruitment module in website preserves each HR
The resume and the resume by mass-election seen, by calculating the matching value of these resumes, HR each selection all is helping to train
Model, industry mark post corporation model is then reused for seldom company of little company and recruitment post.
(4) adaptive algorithm and Project Realization：The overall architecture of Project Realization is by data acquisition, and data prepare and data should
With composition；The data source of data acquisition front has Cassandra databases, MSSQL databases, Mongo databases.
Cassandra databases, MSSQL databases, Mongo databases are distributed in multiple data centers, and the first step allows these data branch
Full dose and incremental backup are held, the processing mode of disparate databases is different, and Cassandra databases are to add report node to collect
Group, MSSQL databases are incremental backups to transit node, and Mongo databases are full backup to transit node,.Transit node
File is transferred to data reporting center using mirror back-up of data instrument rsync, then returns to report MSSQL nodes therefrom
With report Mongo nodes.The effect at data reporting center is to complete big data calculating task in whole group.Data reporting center
According to calculating task, more cost-effective server is selected as core.In data acquisition phase, data reporting center is replicated
Data from data center, and intactly in local recovery；Data preparation layer uses Kettle as ETL,
Kettle is powerful, supports a variety of data formats.It has the definitional language of oneself, just can be opened to intuitive and convenient without writing code
Send out conversion logic.DW is from Vertica.Vertica is preferable as column storage performances, equally also supports relational database
Join operation.
DM Data Markets are realized with Cassandra.DM is completely in accordance with service definition data.It has two kinds of forms, Yi Zhongshi
Big record, includes field as much as possible.Another is facet.Data are preserved using key-value pair.Each application can establish
The Data Market of oneself, data can also be used from a number of other markets.Vertica to DM conversion is usually to be completed by ETL
's.Current conversion is substantially the basic variation of data format.DM to DM conversion, it is often accompanied with data analysis and adds with secondary
Work.Current conversion is completed by Spark.
Data application：The data calculated through Spark, it is stored in the DM of oneself.These data can be analyzed, and be carried
Supply front end applications etc..It is real-time query (adhoc-query) to be exported through commonly used three, Data panel (dashboard),
Data gateway (data-gateway).The above two are traditional BA work.Data gateway is realization of the data as service.
When conventional front-end inquires about data, engineer needs to know the framework of rear end and technology, such as type of database,
Query statement etc..Such case, engineer need to understand ins and outs too much, and the control to quality just has very high risk.
Because we can not have the technical higher as received basis such as too high request, query optimization to the database level of front end engineer
Amount cannot ensure.The more complicated behaviour of operation scenario, particularly integration across database of a variety of heterogeneous databases in modern system be present
Make.We need uniform data service interface, with it is a kind of can be with the standard syntax operation data of Flexible Query.This service interface
The multitype database of bottom is shielded, and can be with Optimizing Queries, there is provided give user unified efficient query interface.We create
One group of RESTfulAPI, using ODATA as query language, complete to perform using memory database, support GET and POST operation
Data.
Data flow is integrated：All these steps need to combine work.Execution each time is defined as one by we
task.Task needs convenient definition, can parallel perform, can inquire about state.We are from airflow as workflow engine.Together
When develop one group of workflow RESTfulAPI, coordinate UI interfaces, there is provided a variety of data task executive modes.
The talent ability for university student crowd is assessed and the method for Postmatch is to be directed to university student's group characteristic
, the recruitment solution using data as core, what we to be solved is quick from the university student of magnanimity and homogeneity resume
Ground is directed to different enterprises, different positions demands, filters out suitable student, and this bag filter contains hard technical ability and soft skill condition,
The overall qualities of student and actual problem-solving ability are emphasized, is the good approach that quality-oriented education result hands to enterprise.
The talent ability for university student crowd is assessed and the method for Postmatch includes algorithm and Project Realization, work
Cheng Shixian has used tactful network and valuation network technology, optimizes the amount of calculation and complexity of whole engineering,.One energy is provided
The Project Realization of rapid feedback result, the data dimension of acquisition is more, and is more suitable for university student crowd；Using approximate real
Simulation goes to evaluate and test student, can more reflect student's objective capability, because more using the pattern of n-person game, such survey
Examination can be in a short time repeatedly without being cracked, and the capacity variation of student can more rapidly, and believable embodiment is in the algorithm；Also adopt
By the use of ranking hundredths as matching value, job hunting is a competitive relation, and relative indicatrix is more meaningful；From talent's supply and demand side to the talent's
It is required that setting out, the big data scheme of personal integration capability matching is paid close attention to, is not only able to tell that job hunter expects the competitiveness of position,
The potential working opportunity that they have no knowledge about is able to tell that, this recommendation is capability-based, saves job hunter's plenty of time cost；
For recruitment person, present mass-election is manually completed, every part of resume general review time 3-20 seconds.So do not only manpower into
This height, and at all bad filter out the really suitable talent.
The foundation of student side individual quality model and enterprises end the position capability model is not merely using evaluation and test and resume
Data, simulated by commercial struggle, evaluate and test and learn to capture multiple dimension datas of the user within a period of time, position matching is
Relative rankings index, for neither one absolute figure it may be said that user is well suited for some position, this ranking index is in single duty
Relative rankings position in the user crowd all applied of position；The realization of engineering is equally the pass that this algorithm can play a role
Key.Its subject matter be no matter user model or Post Model, it is various dimensions, and new dimension ceaselessly adds again
In adding.The data of these dimensions have polytype, including circumferential edge, and data volume is big and is inconvenient to handle.Note as one
Record may have hundreds of indexs.Such million users, the matching of million positions, the size of data being related to reach P ranks,
Need to use the reduction amount of calculation of tactful network and value network.
The present invention has used big data matching algorithm, and personal quality model and post capability model are calculated into matching degree, and
And everyone competitiveness to a specific position and application ranking are drawn using this data, there is ability of self-teaching, energy
It is enough to be relied primarily at this stage by training and use, the raising degree of accuracy, the match selection solved between mass talent and post
The problem of HR artificial mass-elections, time cost is saved, has improved efficiency, and has reached more preferable effect.
The better embodiment of this patent is explained in detail above, but this patent is not limited to above-mentioned embodiment party
Formula, can also be on the premise of this patent objective not be departed from one skilled in the relevant art's possessed knowledge
Various changes can be made.
Claims (2)
1. a kind of talent ability for university student crowd is assessed and the method for Postmatch, it is characterised in that specific steps are such as
Under：
(1) establishment of student side individual quality model：The use of student side individual quality model teaches-simulation-and puts into practice model, teach
Module is teaching for online content, and analog module is soft or hard using analog, experience type teaching and evaluation and test acquisition Students ' Comprehensive
Technical ability, put into practice the Project chance that module is supplied to students ' actual situation enterprise；The analog module includes simulation tool and evaluation and test
Instrument, analog module is by online commercial struggle simulation system from data analysis, business sensitive degree, financial affairs control, the dimension of strategic decision
Degree obtain student business technical ability evaluation, analog module by personal evaluating system from individual leadership power, ditch air grating, cooperation wind
The dimension of lattice obtains the personal soft skill evaluation of student；
(2) establishment of enterprises end position capability model：The position capability model includes two kinds of basic capacity models and specific energy
Power model, basic capacity model include basic skill set requirements and corporate culture, and certain capabilities model includes the skill in specific post
It can require；The data of the employee of outstanding performance on existing recruitment post are gathered by enterprise HR, the collection of the data passes through simulation
Completed with evaluation and test, while gather post performance Judgement Matrix, the general character in these data is included into the basic capacity model of company,
Remainder data is included into post capability model；
(3) matching and marking algorithm：From enterprises end position capability model, the relation that linear regression goes out between each variable,
Algorithm of giving a mark calculates each student in the ability value of each position, and then sort proprietary score, is matched with hundredths
Index is spent, the above-mentioned algorithm of overall crowd's repetition has been applied for plus all, has drawn competitiveness ranking；
(4) adaptive algorithm and Project Realization：The overall architecture of Project Realization is by data acquisition, and data prepare and data application group
Into.
2. the talent ability according to claim 1 for university student crowd is assessed and the method for Postmatch, its feature
It is, the module of teaching includes network opening course MOOC modules, case module and exercise module, and system is by practising mould
The data that block collection student grasps to knowledge point.
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| CN108171449A (en) * | 2018-03-03 | 2018-06-15 | 成都中空间科技有限公司 | Recommendation Employment System based on rural migrant worker's construction level |
| CN108564291A (en) * | 2018-04-20 | 2018-09-21 | 杭州恒生数字设备科技有限公司 | A kind of students'growth process evaluation system based on area's chain block |
| CN108596420A (en) * | 2018-02-02 | 2018-09-28 | 武汉文都创新教育研究院（有限合伙） | A kind of talent assessment system and method for Behavior-based control |
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| CN108805533A (en) * | 2018-06-07 | 2018-11-13 | 厦门华厦学院 | A kind of talent ability assessment recommendation platform based on big data |
| CN108829676A (en) * | 2018-06-11 | 2018-11-16 | 安徽引航科技有限公司 | Talent's professional ability appraisal procedure based on text analysis technique |
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| CN108564291B (en) * | 2018-04-20 | 2020-11-27 | 杭州恒生数字设备科技有限公司 | Student growth process evaluation system based on district chain block |
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| CN108647294A (en) * | 2018-05-07 | 2018-10-12 | 韦玮 | Information recommendation system |
| CN108805533A (en) * | 2018-06-07 | 2018-11-13 | 厦门华厦学院 | A kind of talent ability assessment recommendation platform based on big data |
| CN108829676A (en) * | 2018-06-11 | 2018-11-16 | 安徽引航科技有限公司 | Talent's professional ability appraisal procedure based on text analysis technique |
| CN109214652A (en) * | 2018-08-06 | 2019-01-15 | 常州天正工业发展股份有限公司 | A kind of post capability calculation method and device |
| CN109272233A (en) * | 2018-09-21 | 2019-01-25 | 长沙理工大学 | A kind of employee's competency appraisal procedure closed based on type-2 fuzzy sets |
| CN109523444A (en) * | 2018-10-11 | 2019-03-26 | 昆山信高圣信息科技有限公司 | A kind of information processing method and device combining university students' innovative undertaking |
| CN109543967A (en) * | 2018-11-08 | 2019-03-29 | 斑马网络技术有限公司 | Assess method, apparatus, system and the storage medium of manpower demand |
| CN113439279A (en) * | 2018-11-19 | 2021-09-24 | 瑞米尼街道公司 | Method and system for providing a multi-dimensional human resources configuration advisor |
| CN111985897A (en) * | 2020-08-20 | 2020-11-24 | 诚智行网络科技(深圳)有限公司 | Method and device for constructing occupational portrait data model by using talent big data |
| CN111985897B (en) * | 2020-08-20 | 2024-01-12 | 诚智行网络科技(深圳)有限公司 | Method and device for constructing professional portrait data model by using talent big data |
| CN112101828A (en) * | 2020-11-23 | 2020-12-18 | 广州万维图灵智能科技有限公司 | Post skill evaluation method, system, electronic device and storage medium |
| CN114723337A (en) * | 2022-05-12 | 2022-07-08 | 青软创新科技集团股份有限公司 | Online professional ability training effect evaluation system and method |
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Application publication date: 20171205 |