CN108335047A

CN108335047A - Carry out the personal competitiveness intelligent evaluation system and method for school's application

Info

Publication number: CN108335047A
Application number: CN201810145377.4A
Authority: CN
Inventors: 莫凌峰
Original assignee: Lotus Root Technology (shenzhen) Co Ltd
Current assignee: Lotus Root Technology (shenzhen) Co Ltd
Priority date: 2018-02-12
Filing date: 2018-02-12
Publication date: 2018-07-27
Also published as: WO2019154305A1

Abstract

The present invention provides a kind of personal competitiveness intelligent evaluation system of progress school application, including：Data acquisition subsystem is used to acquire the score factor data of passing applicant and receives the score factor data of present application person；Competitiveness scoring subsystem is used to determine the synthesized competitiveness standard total score and competitiveness grade of present application person；Data modeling and analyzing subsystem be used to establish application winner's model of each school and calculate the corresponding each school of present application person by admission probability；Analysis of selecting a school is used to, according to the synthesized competitiveness standard total score of present application person, competitiveness grade and by admission probability, generate the analysis report of selecting a school of present application person with application subsystem.The present invention also provides a kind of personal competitiveness intelligent evaluation methods of progress school application.The present invention solves the problems, such as that existing school's application consulting tool can not carry out the personal analysis on competitive of admission by application in conjunction with the unstructured data of applicant.

Description

Carry out the personal competitiveness intelligent evaluation system and method for school's application

Technical field

The present invention relates to technical field of information processing more particularly to a kind of personal competitiveness carrying out school's application intelligently to comment Estimate system and method.

Background technology

It, can be to the development of life into school (such as all kinds of universities either institute) study or pursuit of advanced studies for many people Generate important role.In general, mainly there are domestic school and external school two major classes in the school entered.And with compatriots' Improvement of living standard, Chinese are learnt or are taken an advanced study to have been formed aboard other than entering domestic Learning in School A kind of new custom.Simultaneously as the Level of Open up of China is continuously improved, increasingly close, foreign country is contacted with external exchanging People carrys out Chinese study abroad or take an advanced study equally as a kind of new trend.

But the personage for much wanting to enter home or overseas Learning in School or pursuit of advanced studies, information is received due to itself Collection, the ability of processing and analysis and related resource are limited, it tends to be difficult to which it is objective that the competitiveness to itself carrying out school's application carries out And comprehensive assessment, also None- identified from carry out school's application when existing weak link, more leisure opinion to weak link into Row improves and is promoted to enhance the personal competitiveness for carrying out school's application.

For studying abroad, much want that the personage studied abroad did not contacted the dependencies gone abroad to study before this, it is right The matters for needing to prepare of going abroad to study are without any idea.Due to study abroad out of trim and to external school's situation no Solution, the applicant studied abroad from main application often while applying more schools to improve the success oneself enrolled for various reasons Rate；And in actual environment, other most non-autonomous application application for studying abroad persons can select to be more familiar with staying for application for studying abroad situation The counseling services for learning service organization, to improve application for studying abroad success rate.

For from the applicant that main application is studied abroad, knows little about it, add due to itself foreign language aptitude and to abroad instance The audit index that upper each school uses when audit is applied is not quite similar again, and such applicant can not often apply full to oneself The school of meaning can not apply to scholarship.And for selecting the applicant of service for studying abroad mechanism assists application, it is each to study abroad The expenses standard and the equal disunity of applicant's Competitiveness Assessment standard of service organization cause applicant often to face complicated selection Predicament and extremely high service acquisition cost.Traditional service for studying abroad mechanism by observation, record and analyzed for a long time Past application result helps applicant to analyze application material to optimize application result, this needs relevant practitioner to have Very sturdy professional knowledge and practical experience, while needing to consume huge man power and material.

Although although traditional consultation on the study abroad tool can help applicant to verify examination for studying abroad score currently on the market, such as GPA (Grade Point Average, grade point average point), TOEFL (The Test of English as a Foreign Language, TOEFL), GRE (Graduate Record Examination, Graduate Record Examinations) achievement etc., And select suitable school for applicant.However, these consulting tools based on structural data cannot to personal work background, Improvement idea is analyzed and provided to extracurricular activities background, academic background or other unstructured datas, to instruct to apply Person is promoted in a certain application for studying abroad operation index field.

The above is only used to facilitate the understanding of the technical scheme, and is not represented and is recognized that the above is existing skill Art.

Invention content

The main purpose of the present invention is to provide a kind of personal competitiveness intelligent evaluation system of progress school application and sides Method, it is intended to which the individual of school's application can not be carried out in conjunction with the unstructured data of applicant by solving existing school's application consulting tool The problem of analysis on competitive.

To achieve the above object, the present invention provides a kind of personal competitiveness intelligent evaluation system of progress school application, packet It includes：User terminal, connection network, database further include：Data acquisition subsystem, competitiveness scoring subsystem, data modeling with Analyzing subsystem, select a school analysis and application subsystem；Wherein,

The data acquisition subsystem, the score factor data for acquiring passing applicant, and pass through the connection Network is connect with the user terminal, receives the score factor data for the present application person that the user terminal is sent, and incited somebody to action The score factor data of the score factor data and present application person toward applicant is stored to the database；

The competitiveness scoring subsystem, for according to the score factor data of passing applicant, present application person The score factor data, determine the synthesized competitiveness standard total score and competitiveness grade of present application person；

The data modeling and analyzing subsystem include modeling module, Success Rate Analysis module；The modeling module, is used for According to the score factor data of the passing applicant of pre-selection school, application winner's model of pre-selection school is established；It is described Success Rate Analysis module, for according to the score factor data of present application person and the application winner of pre-selection school Model, calculate present application person correspond to pre-selection school by admission probability；

Select a school analysis and the application subsystem, for determining that present application person corresponds to the Competitiveness plan of pre-selection school Slightly；And generate the analysis report of selecting a school of present application person.

Preferably, the corresponding score of the score factor data wants the prime implicant to include：Background information, is lived at academic aptitude after class Dynamic, standardization examination and other predetermined materials.

Preferably, the competitiveness scoring subsystem includes the total sub-module of competitiveness, competitiveness grade module；Wherein,

The total sub-module of competitiveness, for according to the score factor data of passing applicant, present application person The score factor data, calculate separately passing applicant respectively score element standard scores, present application person each score element mark Standard point；According to passing applicant respectively score element standard scores, present application person each score element standard scores, calculate present application The synthesized competitiveness standard total score of person；

The competitiveness grade module, for according to the synthesized competitiveness standard total score of passing applicant, current Shen Please person the synthesized competitiveness standard total score, determine the competitiveness grade of present application person；And according to passing application The score factor data of person, determines the level of strength grade of each school.Preferably, analysis and the application subsystem of selecting a school System includes analysis module of selecting a school；

The analysis module of selecting a school calculates correspondence and takes as an elective course in advance for the score factor data by changing present application person The enhancing rate by admission probability in school；According to by the enhancing rate of admission probability, determine that corresponding pre-selection the optimal of school promotes meter Sub-element item and corresponding Competitiveness strategy.

Preferably, the analysis module of selecting a school is additionally operable to according to the application winner model of pre-selection school and current The score factor data of applicant determines that present application person corresponds to the weak score of application winner's model of pre-selection school Prime implicant is wanted, and determines corresponding Competitiveness strategy.

Preferably, the analysis report of selecting a school of present application person corresponds to the quilt of pre-selection school including at least present application person Enroll probability and/or Competitiveness strategy and/or synthesized competitiveness standard total score and/or competitiveness grade.

Preferably, the data modeling and analyzing subsystem further include model optimization module；Wherein,

The model optimization module, for based on default test data, being determined and being competed according to application winner's model Power prediction result, and obtain the competitiveness result that the competitiveness scoring subsystem is determined based on the default test data；It will The competitiveness prediction result is compared with the competitiveness result, and according to obtain comparison result assessment it is described application at The accuracy of work(person's model, to obtain Accuracy evaluation result；According to the Accuracy evaluation as a result, optimizing described apply successfully Person's model.

In addition, to achieve the above object, the present invention also provides a kind of personal competitiveness intelligent evaluations of progress school application Method, including：

The score factor data of passing applicant is acquired, and receives the score factor data of present application person, and incited somebody to action The score factor data of the score factor data and present application person toward applicant is stored to database；

According to the score factor data of passing applicant, the score factor data of present application person, determination is worked as The synthesized competitiveness standard total score and competitiveness grade of preceding applicant；

According to the score factor data of the passing applicant of pre-selection school, application winner's mould of pre-selection school is established Type；

Worked as according to the score factor data of present application person and the application winner model of pre-selection school, calculating Preceding applicant correspond to pre-selection school by admission probability；

Determine that present application person corresponds to the Competitiveness strategy of pre-selection school；And generate selecting a school point for present application person Analysis report.

Preferably, the score factor data according to passing applicant, present application person the score element The step of data, the synthesized competitiveness standard total score and competitiveness grade that determine present application person includes：

According to the score factor data of passing applicant, the score factor data of present application person, count respectively Calculate passing applicant respectively score element standard scores, present application person each score element standard scores；

According to passing applicant respectively score element standard scores, present application person each score element standard scores, calculate current The synthesized competitiveness standard total score of applicant；

According to the synthesized competitiveness standard total score of passing applicant, the synthesized competitiveness standard of present application person Total score determines the competitiveness grade of present application person；

And the score factor data according to passing applicant, determine the level of strength grade of each school.

Preferably, the determining present application person corresponds to the step of the Competitiveness strategy of pre-selection school, specifically includes： The analysis module of selecting a school by changing the score factor data of present application person, calculate corresponding pre-selection school by admission probability Enhancing rate；It optimal promote score according to by the enhancing rate of admission probability, determine corresponding pre-selection school and wants prime implicant and correspondence Competitiveness strategy；

Alternatively, according to the application winner model of pre-selection school and the score factor data of present application person, It determines that prime implicant is wanted in the weak score of application winner's model of present application person's correspondence pre-selection school, and determines corresponding competition Power Promotion Strategy.

The personal competitiveness intelligent evaluation system and method for a kind of carry out school application that the embodiment of the present invention proposes, will be with The highly relevant key unstructured data of application for studying abroad and structural data are incorporated into score factor data, and largely adopt Collect the score factor data of passing applicant.Based on the score factor data of a large amount of passing applicants, and score factor data In unstructured data quantization, accurately analyze the level of competitiveness of present application person and corresponding different level of strength etc. Grade school by admission probability, compensate for existing school's application consulting tool can not in conjunction with applicant unstructured data into The deficiency of row individual application school analysis on competitive.Meanwhile also provide for present application person it is corresponding with pre-selection school accurate Effective Competitiveness strategy, level of competitiveness information (including synthesized competitiveness standard total score, the ranking in default group Situation, competitiveness grade) and convenient analysis report of intuitively selecting a school, to for provide the applicant school apply it is abundant directly It sees, accurately and effectively personal Competitiveness Assessment information contributes to applicant preferably to make school Shen to carry out decision references It please decision and increase application success rate.The embodiment of the present invention realizes the online school's application consulting of one-stop intelligent, is learned with tradition School application consulting needs the face-to-face of height or different from consultant's exchange online, save applicant exchanged with consultant it is numerous Trivial flow and high communication cost help applicant to realize analysis on competitive on self-service line, find out shortcomings and provide The a whole set of lines such as improvement strategy, online application and application result tracking, which are gone to school, to be applied preparing overall process.

Description of the drawings

Fig. 1 is the personal competitiveness intelligent evaluation system block diagram that the present invention carries out school's application；

Fig. 2 is the implementation flow chart for the personal competitiveness intelligent evaluation that the present invention carries out school's application；

Fig. 3 is the reality of the analysis report of selecting a school for the personal competitiveness intelligent evaluation system generation that the present invention carries out school's application Existing schematic diagram；

Fig. 4 is the flow signal for the personal competitiveness intelligent evaluation method first embodiment that the present invention carries out school's application Figure；

Fig. 5 is the flow signal for the personal competitiveness intelligent evaluation method second embodiment that the present invention carries out school's application Figure.

The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.

Specific implementation mode

It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.

Since existing school application consulting tool can not carry out individual application school in conjunction with the unstructured data of applicant Analysis on competitive, the present invention provide a solution, that is, provide a kind of personal competitiveness intelligent evaluation of progress school application System and method.

It should be noted that a kind of personal competitiveness intelligent evaluation system carrying out school's application of the embodiment of the present invention and side Method usable condition includes but not limited to：(1) apply for the personal competitiveness intelligent evaluation of national school；(2) school outside applicant country Personal competitiveness intelligent evaluation.Wherein, the school is a wide in range property concept, such as all kinds of primary schools, junior middle school, senior middle school, university, Institute, research institute/institute, Training and Learning mechanism.In addition, the type for carrying out school's application further includes application of transfeing to another school.

As shown in Figure 1, a kind of personal competitiveness intelligent evaluation system of carry out school application of the present invention includes：User is whole End 100, connection network 200, database 300, server 400, the personal competitiveness intelligent evaluation system for carrying out school's application System further includes：Data acquisition subsystem 500, data modeling and analyzing subsystem 700, is selected a school point at competitiveness scoring subsystem 600 Analysis and application subsystem 800.

In the following, the implementation flow chart in conjunction with the personal competitiveness intelligent evaluation of progress school shown in Fig. 2 application carries out in detail It describes in detail bright.

Wherein, user terminal 100 can be smart mobile phone, tablet computer, laptop, desktop computer or other electricity Sub-device, by user terminal 100, the relevant treatment of data, such as specific operation circle in user terminal may be implemented in user Face, present application person are inputted, are uploaded, are obtained, are retrieved and changed specific data, such as factor data of scoring, specific to count Sub-element data meaning is described further below.User inputs and the data of the specific data of modification and automatic collection are stored In database 300；Further, it is also possible to control the power of amendment to storing data according to the different stage of user and role's setting Limit.

It can be the packet switching network to connect network 200, for the communication information to be transmitted to other devices from a certain device, also Phone or Internet service can be provided.

Database 300 can be local type database or distributed cloud storage database.

Server 400 can be the network server for possessing processor and memory, and quantity can be one or more.

Data acquisition subsystem 500, the score factor data for acquiring passing applicant, and pass through the connection net Network 200 is connect with the user terminal 100, receives the score factor data of the present application person of the transmission of the user terminal 100, And the score factor data of the score factor data of passing applicant and present application person is stored to the data Library 300；

Wherein, the score factor data is the Critical Examination data that applicant carries out school's application, is generally comprised each Class school is directed to the general key examination data of applicant.In some embodiments, the corresponding meter of the score factor data Sub-element item includes：Background information, academic aptitude, extracurricular activities, standardization examination and other predetermined materials.It should be noted that It is that the score factor data involved in various embodiments of the present invention includes structural data and unstructured data.Structural data For the data that can directly quantify, such as the achievement score of standardization examination；Unstructured data is the data that can not directly quantify, It needs to carry out artificially to convert and can just become the extracurricular activities data such as quantized data, such as volunteer's experience, work experience.

It includes different meter molecular constituents items that prime implicant is wanted in each score, can be according to the types of schools or assessment specifically applied It needs to carry out self-defined setting and increase and decrease, is specifically including but not limited to following content：

Background information includes at least：Once with regard to studying in high school, once with regard to studying in college, once department's academic reputation ranking with regard to studying in college；

Academic aptitude, including but not limited to senior middle school GPA, university GPA, university professional GPA, grade/class's ranking, honor class (A is history, social science, and B is English, and C is mathematics, and D is laboratory science, and E is except English for journey (AP/Honor), A-G subjects Except language, F be vision and art of acting, G be preparatory course elective course), scientific research experience, publish thesis situation；

Extracurricular activities, including community activity, sports, artistic talent, leaders' activities, preparatory course situation, volunteer experience, Work experience；

Standardization examination, including AP/Honor achievements, TOEFL achievements, IELTS achievements, SAT achievements, SAT professional tests (SAT Subject) achievement, ACT achievements, GRE achievements, GRE professional tests achievement, GMAT achievements, LSAT achievements and other language With professional test result；

Other predetermined materials, including but not limited to：Prize-winning situation, personal progress trend, recommendation, recommendation letter.Wherein, it obtains Prize situation is used to reflect the significance level that applicant obtains awards；Individual's progress trend is used to reflect school work/science of applicant Progress and promoted situation；Recommendation is used to reflect the extraneous personal evaluation for applicant；Recommendation letter is for reflecting applicant Description and self-assessment for itself.For example, if applicant undergraduate course learn during obtain respectively it is provincial, national, International totally three academic awards, and the academic importance of above three awards is incremented by successively, then in the prize-winning of evaluation applicant When situation, the corresponding score of academic awards of different academic importance is given, and respective weights are set according to awards importance, is obtained Applicant is obtained in the total score of situation element of winning a prize, to carry out quantum chemical method and analysis to the prize-winning situation of applicant.

Above-mentioned passing applicant includes the applicant over the years for once carrying out the application of same class school, such as to present application Person study abroad application competitiveness intelligent evaluation when, passing applicant should select passing once to carry out Shen of studying abroad Applicant please；When carrying out the competitiveness intelligent evaluation of national university master application to present application person, passing applicant answers Select the passing applicant for once carrying out national university master application.If a certain passing applicant's success is recorded by a certain school It takes, then by the passing applicant labeled as " application winner ".The score factor data of present application person is logical for present application person Cross the score factor data of the upload of user terminal 100.

Specifically, data acquisition subsystem 500, including：Data-pushing module 510, data collection module 520, data connect Receive module 530.Wherein, data-pushing module 510 is used to predefined score feature category pushing to user terminal 100；This Sample, present application person input relevant score factor data, user by user terminal 100 according to the score feature category of push Relevant score factor data is uploaded to data reception module 530 by terminal 100.

Data acquisition module 520, the score factor data for acquiring passing applicant over the years.Passing applicant's over the years Score factor data includes the structuring score factor data of passing applicant over the years and unstructured score factor data.It is passing Further include school's public data in the score factor data of applicant.Wherein, school's public data includes what corresponding school announced The structural data and unstructured data enrolled over the years, such as school geographical location, tuition fee situation, admission condition, department Art reputation ranking enrolls number, the background information data of Accepted Applicants, academic aptitude data, extracurricular activities data, standardization over the years Examination data and other predetermined material data.Specifically, data acquisition module 520 uses big data acquisition technique, largely adopts Collect and analyze the score factor data of applicant over the years.

Data reception module 530, the score factor data for receiving the transmission of user terminal 100.In addition, passing Shen over the years Please the score factor data of person and the score factor data of present application person be stored in database 300；It is wanted when needing to call to score Prime number according to when, call the above-mentioned score factor data that stores in database 300.

The competitiveness scoring subsystem 600, for according to the score factor data of passing applicant, present application The score factor data of person determines the synthesized competitiveness standard total score and competitiveness grade of present application person；

Specifically, competitiveness scoring subsystem 600 includes the total sub-module 610 of competitiveness, competitiveness grade module 620.

The total sub-module 610 of competitiveness, for according to the score factor data of passing applicant, present application person The score factor data, calculate separately passing applicant respectively score element standard scores, present application person each score element Standard scores；According to passing applicant respectively score element standard scores, present application person each score element standard scores, calculated separately The synthesized competitiveness standard total score of past applicant, the synthesized competitiveness standard total score of present application person；And according to current The synthesized competitiveness standard total score of applicant determines ranking of the present application person in default group；

In the following, being illustrated (by taking individual application overseas university as an example) in conjunction with a preferred embodiment.

(1) according to division rule is preset, each meter molecular constituents item in prime implicant to carry out distinguishing hierarchy, Yi Zhongyou score The dividing condition of choosing is as shown in table 1.

Table 1

For example, in education background item, every ranking (including once with regard to studying in high school ranking, once attending school University Rank, once The department's academic reputation ranking just studied in college) it is the overall ranking that related authority on education rating organization announces.If present application person Be once first 60 with regard to studying in high school ranking, then present application person once belonged to the 4th layer with regard to studying in high school ranking item, other levels Divide and so on.In another example GPA (Grade Point Average) i.e. Average Score-Points, are one for assessing student performance A index, conversion method are that the obtained achievement of every subjects is scaled point, are carried out according still further to the credit ratio of each subject Weighted sum, acquired results divided by each subject credit summation can be obtained Average Score-Point.Using four point system GPA systems in table 1 System, including the first level (GPA be equal to 3.8 or more), the second level (GPA is equal to 3.7 or more), (GPA is equal to third level 3.6 or more), the 4th level (GPA is equal to 3.5 or more), layer 5 (GPA is equal to 3.3 or more), layer 6 time (GPA Equal to 3.2 or more), layer 7 time (GPA is less than 3.2).

It assigns each hierarchical data of every sub- element in table 1 to corresponding level parameter and weight coefficient, passes through weighting The mode of summation seeks each meter molecular constituents score Pi (e) that prime implicant is wanted in a certain score of present application person, and calculation formula is：

Pi (e)=∑ (each meter molecular constituents maximum value * weight coefficient * level parameters)

Then, each meter molecular constituents score Pi (e) that prime implicant is wanted based on a certain score of present application person, passes through criterion score Routine seek each score element standard scores Pi (es) that mode calculates present application person.It is the prior art that routine, which seeks mode, It no longer repeats one by one herein.

Then, according to each score element score Pi (e), synthesized competitiveness total score P (t) is calculated.Specific calculation It is as follows：

Each score element score Pi (e) is multiplied by a score element weight coefficient respectively, respectively obtains each product；It will Each product addition summation, acquired results are synthesized competitiveness total score P (t).Specific score element weight coefficient does not limit System.In this manner it is possible to obtain the synthesized competitiveness total score P (t) of present application person (or passing applicant).

In this manner it is possible to obtain the synthesis of present application person (or passing applicant) by way of calculating criterion score Competitiveness standard total score P (ts).The synthesized competitiveness standard total score P (ts) of present application person can objectively reflect current Shen Please person level of competitiveness.

Then, according to the synthesized competitiveness standard total score P (ts) of present application person, determine present application person in default group In ranking.

Specifically, according to the synthesized competitiveness standard total score of present application person and be included in calculating applicant it is (passing Applicant adds present application person) sum, ranking of the present application person in passing applicant can be easily obtained, To accurately depict level of competitiveness of the present application person relative to passing applicant.Further, it is also possible to by obtain with Present application person's the same year carries out the most of school's application or all the score factor data of other applicants, and calculates current The synthesized competitiveness standard total score that applicant applies in current year, to obtain ranking of the present application person in current year applicant Situation, and then easily determine level of competitiveness of the present application person relative to current year applicant, current year school's application is provided Reference information.

Further, the competitiveness grade module 620, for the synthesized competitiveness standard according to passing applicant Total score, present application person the synthesized competitiveness standard total score, determine the competitiveness grade of present application person；

In some specific implementations, competitiveness grade module 620 is total to the synthesized competitiveness standard of all passing applicants Divide P (ts) to carry out score range division, is divided into different score value sections；Wherein, different score value sections corresponds to different competitions Power grade, such as poor, general, relatively strong, very strong, extremely strong five grades.Preferably, according to preset ratio to all passing applications The synthesized competitiveness standard total score P (ts) of person carries out score range division.In the synthesized competitiveness mark for calculating present application person After quasi- total score P (ts), corresponding score range is matched, so that it is determined that the competitiveness grade of present application person.

Further, the competitiveness grade module 620 is additionally operable to want prime number according to the score of passing applicant According to determining the level of strength grade of each school；

I.e. in the level of strength grade for determining a certain school, it is over the years that the school is filtered out from all passing applicants Apply for winner, and seeks each meter molecular constituents score Pi of school application winner over the years successively according to the method described above (e), synthesized competitiveness standard total score P (ts) and competitiveness grade.In the level of strength grade for determining each school, preferably Ground first calculates the average value of the synthesized competitiveness standard total score P (ts) of each school application winner over the years, then to each The average value of the synthesized competitiveness standard total score P (ts) of school application winner over the years carries out score range division, is divided into not Same score value section；Wherein, different score value sections corresponds to different level of strength grades, such as five grades of A, B, C, D, E. It should be noted that since the score factor data of the annual application winner of each school may change, in determination When the level of strength grade of school of each institute, the score factor data of school application winner over the years need to be regularly updated, to protect Demonstrate,prove the accuracy of school's level of strength grade.

In addition, other than the method for the level of strength grade of each school of above-mentioned determination, authoritative institution can also be quoted School's level of strength ranking results of publication determine the level of strength grade of each school.

The data modeling includes modeling module 710, Success Rate Analysis module 720 with analyzing subsystem 700；The modeling Module 710 establishes the application success of pre-selection school for the score factor data according to the passing applicant for preselecting school Person's model；Wherein, pre-selection school is the school of school or system recommendation that present application person selectes, i.e., by preselecting several School carries out the personal competitiveness intelligent evaluation of school's application, finally obtains of present application person corresponding with each pre-selection school People's Competitiveness Assessment result.

In some specific implementations, modeling module 710 is calculated according to the score factor data and default modeling of passing applicant Method establishes application winner's model of pre-selection school；Wherein, the preferred Bayesian Classification Arithmetic of modeling algorithm is preset.That is modeling module 710 based on the score factor data of the passing applicant person of acquisition, and the score factor data of passing applicant is divided Class stores, then extracts each passing applicant each of score component attributes and index by data mining algorithm, so as into Row data analysis and modeling.The data mining algorithm includes but not limited to following algorithm：Decision tree analysis algorithm, neural network Parser (neural network algorithm), cluster algorithm, Association Rule Analysis algorithm, logistical regression Parser (Logistic regression algorithm).

In some specific implementations, modeling module 710 will be in a certain level of strength grade by decision tree analysis algorithm School all passing applicants correlometer sub-element data (including score component attributes and corresponding achievement data) into Row analysis, to obtain all factors to applying for successfully and applying the influence correlation to fail.Then, pass through cluster algorithm Analyze application winner and application loser respectively possessed by peculiar common score factor data (including score component attributes And corresponding achievement data).The above two alanysis result is combined and sorts and establish several application winner's models, then By the way that applying successfully being sampled with randomly drawing sample in the database of two class people of loser, winner's model is applied in test Accuracy rate, and using the highest application winner model of accuracy rate as to present application person carry out by admission probabilistic forecasting Application winner's model.

Further, the Success Rate Analysis module 720, for according to the score factor data of present application person and Preselect school the application winner model, calculate present application person correspond to pre-selection school by admission probability；

In some specific implementations, Success Rate Analysis module 720 is based on application winner's model, to the meter of present application person Sub-element data carry out operation, analysis obtain present application person correspond to different effectively schools by admission probability.

Further, select a school analysis and the application subsystem 800, for determining that present application person corresponds to pre-selection school Competitiveness strategy；And generate the analysis report of selecting a school of present application person.

Determine that present application person corresponds to the Competitiveness strategy of pre-selection school, it is therefore intended that：It is provided to applicant polygonal Degree has constructive and enforceability Competitiveness strategy, to contribute to applicant to understand the competitiveness feelings of itself Condition, and targetedly improvement and promotion activity are made using the Competitiveness strategy of offer, contribute to the Shen for increasing applicant It please success rate.

In some specific implementations, the analysis report of selecting a school of present application person corresponds in advance including at least present application person Take as an elective course school by admission probability and Competitiveness strategy.

It should be noted that since many schools are equipped with application student enrollment limit, and many schools for specific state The foreign student of family also is provided with admission limit.Therefore, only provide present application person correspond to pre-selection school by admission probability, can not Fully comprehensive reference information is provided to present application person.The present invention and existing traditional artificial consultation way or on-line consulting Mode that system is seeked advice from the difference is that, intelligent evaluation system of the invention not only provides to present application person intuitive Personal overall ranking and ranking in its residing competitiveness grade, moreover it is possible to provided to present application person by way of brushing and selecting The home ranking in current year applicant.That is, the intelligent evaluation system of the present invention can be based on present application person and other Shens Please person (including passing applicant and current year applicant) score element, the synthesized competitiveness standard for calculating present application person is total Divide P (ts), competitiveness grade, and can further obtain ranking of the present application person under all kinds of ranked categories, from And so that present application person grasps itself abundant and comprehensive level of competitiveness information, to be more advantageous to decision references.Therefore, Can also include synthesized competitiveness standard total score P (ts), competitiveness grade and correlation in the analysis report of selecting a school of present application person Ranking.

It may include itself level of competitiveness information (including the comprehensive competition of present application person in the i.e. described analysis report of selecting a school Power standard total score P (ts), competitiveness grade and relevant ranking), present application person correspond to being enrolled for several schools Probability, Competitiveness strategy, output format can include but is not limited to html, doc, xml, pdf.In addition, described select a school Analysis report can also include the relevant visualization datagram/table of analysis on competitive result of present application person.It is described to select a school point Analysis is reported：According to arranged by admission probability inverted order school recommendation's list, competitiveness grade close school The correspondence associated service provider of recommendation list and suggested design links.Select a school the analysis report signal such as Fig. 3 specifically generated It is shown, wherein Competitiveness policy section only generates corresponding Competitiveness so that applicant selects application first school as an example Strategy produces corresponding Competitiveness strategy for each pre-selection school of applicant's selection in practical operation.

In addition, the analysis of selecting a school further includes pushing module 820 with application subsystem 800；The pushing module 820 is used for Analysis report of selecting a school described in present application person is sent to the user terminal 100.Active user is connect by user terminal 100 Midwifery is at analysis report of selecting a school, to know the competitiveness result of itself, enroll probabilistic information by selected target school.

In addition, the analysis of selecting a school further includes application module 830 with application subsystem 800；The application module 830 is used The relevant school of present application person is applied operating in realizing.For example, being carried out to the application materials that present application person submits preliminary It examines；And submit the application material of present application person to official's application for enrollment in a school system；And the application of inquiry present application person State.

The personal competitiveness intelligent evaluation system for carrying out school's application that the present embodiment is related to will apply for height phase with school The key unstructured data and structural data closed is incorporated into score factor data, and largely acquires passing applicant's Score factor data.Based on the unstructured number in the score factor data of a large amount of passing applicants, and score factor data According to quantization, accurately analyze the level of competitiveness of present application person and being enrolled for corresponding different level of strength grades school Probability, compensating for existing study application consulting tool can not combine the personal school's application of the unstructured data progress of applicant competing Strive the deficiency of power analysis.Meanwhile also accurately and effectively Competitiveness strategy and convenience are provided for present application person intuitively Select a school analysis report and solution, to for provide the applicant abundant intuitive, the accurately and effectively individuals that school apply Competitiveness Assessment information contributes to applicant preferably to make school's application decision and increases application to carry out decision references Success rate.The embodiment of the present invention realizes the online school's application consulting of one-stop intelligent, applies for that consulting (is such as studied abroad with traditional school Consulting) the face-to-face of height or different from consultant's exchange online is needed, save the cumbersome stream that applicant exchanges with consultant Journey and high communication cost help applicant to realize analysis on competitive on self-service line, find out shortcomings and provide improvement School's application on a whole set of lines such as strategy, online application and application result tracking prepares overall process.

Further, as shown in Figure 1 and Figure 2, the analysis of selecting a school includes analysis module of selecting a school with application subsystem 800 810；

Analysis module of selecting a school 810, it is corresponding for determining that present application person corresponds to the Competitiveness strategy of pre-selection school Realization method is a variety of, such as：

In some specific implementations, the analysis module 810 of selecting a school, for the score element by changing present application person Data calculate the enhancing rate by admission probability of corresponding pre-selection school；According to by the enhancing rate of admission probability, corresponding pre-selection is determined The optimal of school promotes score and wants prime implicant and corresponding Competitiveness strategy.

The change for investigating any one score factor data, for preselecting the promotion effect by admission probability of school；If The more apparent by admission probability enhancing rate of school is preselected, then it is more excellent that prime implicant is wanted in the corresponding score of score factor data changed Or prime implicant is wanted in the optimal score that promoted.In other words, it indicates can effectively improve to present application person and is preselected school's admission generally The correspondence direction of improvement of rate, to formulate corresponding Competitiveness strategy.

For example, leaders' activities active index is promoted to 3 points from current 2 points, present application person is recorded by a certain pre-selection school The probability taken is promoted to 65% from 60%；And the quantity that publishes thesis (the first authors) is from when being promoted to 2 for 1, by admission probability 85% can be promoted to.Then obviously, present application person should more promote emphatically the quantity (the first authors) that publishes thesis, to improve quilt Enroll probability.Others score factor data and so on, the corresponding enhancing rate by admission probability is obtained, it is most advantageous to find Prime implicant is wanted by the promotion score of admission probability in present application person's raising corresponding pre-selection school.

In other specific implementations, the analysis module 810 of selecting a school, be additionally operable to according to pre-selection school the application at Work(person model and the score factor data of present application person determine that present application person corresponds to the application winner of pre-selection school Prime implicant is wanted in the weak score of model, and determines corresponding Competitiveness strategy.

Since the application winner model of pre-selection school can totally reflect the group of the application winner of pre-selection school Average point (the meter molecular constituents score of the application winner of each pre-selection school of prime implicant is wanted in average case, including each score Average value).Each score factor data of present application person is wanted into the average mark of prime implicant with each score of winner's model is applied for Standard point is compared, and prime implicant is wanted in the weak score for more easily finding out present application person, and convenience of calculation is accurate.According to finding out Weak score want prime implicant, provide constructive Competitiveness strategy (including specific Optimizing Suggestions) to present application person, To improve the data that prime implicant is wanted in weak score.For example, the TOEFL achievements 95 of present application person are divided, hence it is evident that pre- taken as an elective course less than certain The TOEFL achievement averages of the application winner in school divide 105 points, then present application person should focus on to improve TOEFL achievements；It is corresponding The Competitiveness strategy on ground, generation includes methods and skills and the executive plan for being improved TOEFL achievements.

Further, it is also possible to according to the synthesized competitiveness standard total score of present application person, the competitiveness grade and institute State by admission probability, find out it is potential can promote score and want prime implicant, and strategic recommendation on improvement is correspondingly provided, so that currently Applicant improves application success rate.

In some specific implementations, according to the synthesized competitiveness standard total score of present application person, described competitiveness etc. Grade and described by admission probability, generates the Competitiveness strategy of present application person.For example, comparing the competitiveness of present application person The corresponding synthesized competitiveness total score of grade synthesized competitiveness total score score value interval limit corresponding with more excellent level-one competitiveness grade Prime implicant is wanted in the score that the score of value, both determining score value gap, and lookup present application person are relatively low, to generate competitiveness Promotion Strategy.For example, if the extracurricular activities score component scores of present application person are relatively low, extracurricular activities are scored element Item wants prime implicant labeled as the improved score of needs.In other words, present application person obtains the Competitiveness plan by user terminal Slightly, and need activity score outside class that the corresponding sub- element item of respectively scoring of prime implicant is wanted to be promoted and reinforced, it is competing to be promoted Strive power level.Further, performability analysis is carried out to the Competitiveness strategy of generation, if analysis result is the competitiveness There is the improved project being difficult to realize in improvement project, then the improved project is labeled to inform present application person.

In some specific implementations, analysis module of selecting a school 810 is additionally operable to the synthesized competitiveness according to present application person Standard total score, the competitiveness grade and described by admission probability, determine the matched school of the level of competitiveness of present application person Level of strength grade；According to the level of strength grade of determining school, the school in the level of strength grade is searched, and Generate the Competitiveness strategy that present application person is enrolled by the school of the level of strength grade.And it searches and is better than above-mentioned reality The school of power hierarchical level, and by the Competitiveness strategy of corresponding school's admission.

In the present embodiment, the personal competitiveness intelligent evaluation system for carrying out school's application provides multi-angle to applicant With constructive and enforceability Competitiveness strategy, to contribute to applicant to understand the competitiveness situation of itself, and Targetedly improvement and promotion activity are made using the Competitiveness strategy of offer, contributes to the application success for increasing applicant Rate.

Further, as shown in Figure 1 and Figure 2, the data modeling and analyzing subsystem 700 further include model optimization module 730；Wherein,

The model optimization module 730, for based on default test data, being determined according to application winner's model competing Power prediction result is striven, and obtains the competitiveness knot that the competitiveness scoring subsystem 600 is determined based on the default test data Fruit；The competitiveness prediction result is compared with the competitiveness result, and according to described in obtained comparison result assessment The accuracy for applying for winner's model, to obtain Accuracy evaluation result；According to the Accuracy evaluation as a result, optimizing the Shen It please winner's model.

After above-mentioned modeler model 710 establishes application winner's model, need constantly to established application winner's mould Type is assessed, with the prediction accuracy of scoring model, to constantly carry out the optimization of model, to realize that best prediction is imitated Fruit.Wherein, when assessing application winner's model, the assessment data of selection are prediction test data, are preferably stored in The score factor data of passing applicant in database 300.For example, by the score of several random passing applicants of selection It is (including but not limited to comprehensive to obtain competitiveness prediction result by applying for that winner's model carries out operation and analysis for factor data Competitiveness total score and competitiveness grade).Then, the score factor data of several random passing applicants of selection is passed through competing The total sub-module 610 of competitiveness striven in power scoring subsystem 600, competitiveness grade module 620 carry out operation and analysis, obtain pair The competitiveness result (including but not limited to synthesized competitiveness total score and competitiveness grade) answered.By competitiveness prediction result and competition Power result is compared, and judges the gap of the two；According to the gap judging result of the two, the prediction of application winner's model is judged Accuracy.

Further, if the prediction accuracy of application winner's model is relatively low, mould is carried out to application winner's model Type optimizes or establishes new application winner's model.Further, it is also possible to be referred to according to other assessments such as the operation stability of model Mark is assessed and is optimized to model.

In this way, constantly carrying out model prediction Accuracy evaluation by the application winner model to foundation, contribute to mould The optimization of type, to ensure to apply for the accuracy of winner's model prediction.

With reference to Fig. 4, the embodiment of the present invention provides a kind of personal competitiveness intelligent evaluation method of progress school application, including Following steps：

Step S10 acquires the score factor data of passing applicant, and prime number is wanted in the score of reception present application person According to, and the score factor data of the score factor data of passing applicant and present application person is stored to data Library；

Wherein, the score factor data is the crucial examination data that applicant carries out school's application, is generally comprised all kinds of School is directed to the general key examination data of applicant.In some embodiments, the corresponding score of the score factor data The prime implicant is wanted to include：Background information, academic aptitude, extracurricular activities, standardization examination and other predetermined materials.It should be noted that Score factor data involved in various embodiments of the present invention includes structural data and unstructured data.Structural data is can With the data directly quantified, such as the achievement score of standardization examination；Unstructured data is the data that can not directly quantify, that is, is needed Artificially convert and can just become the extracurricular activities data such as quantized data, such as volunteer's experience, work experience.

Other predetermined materials, including but not limited to：Prize-winning situation, personal progress trend, recommendation, recommendation letter.Wherein, it obtains Prize situation is used to reflect the significance level that applicant obtains awards；Individual's progress trend is used to reflect school work/science of applicant Progress and promoted situation；Recommendation is used to reflect the extraneous personal evaluation for applicant；Recommendation letter is for reflecting applicant Description and self-assessment for itself.For example, if applicant undergraduate course learn during obtain respectively it is provincial, national, International totally three academic awards, and the academic importance of above three awards is incremented by successively, then in the prize-winning of evaluation applicant When situation, the corresponding score of academic awards of different academic importance is given, and respective weights are set according to awards importance, is asked Take applicant in the total score of prize-winning situation element, to carry out quantum chemical method and analysis to the prize-winning situation of applicant.

Above-mentioned passing applicant includes the applicant over the years for once carrying out the application of same class school, such as to present application Person study abroad application competitiveness intelligent evaluation when, passing applicant should select passing once to carry out Shen of studying abroad Applicant please；When carrying out the competitiveness intelligent evaluation of national university master application to present application person, passing applicant answers Select the passing applicant for once carrying out national university master application.If a certain passing applicant's success is recorded by a certain school It takes, then by the passing applicant labeled as " application winner ".Wherein, the score factor data of present application person is present application The score factor data that person passes through user terminal uploads, wherein user terminal can be smart mobile phone, tablet computer, notebook Computer, desktop computer or other electronic devices, by user terminal, user may be implemented the relevant treatment of data, such as The specific operation interface of user terminal, present application person is inputted, is uploaded, is obtained, is retrieved and changed specific data, such as is counted Sub-element data, specific factor data meaning of scoring are described further below.User input and modification specific data and The data of automatic collection are stored in database；Further, it is also possible to be controlled according to the different stage of user and role's setting To storing the modification authority of data.

The score factor data of passing applicant over the years include passing applicant over the years structuring score factor data with Unstructured score factor data.Further include school's public data in the score factor data of passing applicant.Wherein, school is public It includes the structural data enrolled over the years and unstructured data that corresponding school announces to open data, such as school geographical location, Tuition fee situation, department's academic reputation ranking, enrolls number, background information data, the academic aptitude of Accepted Applicants at admission condition over the years Data, extracurricular activities data, standardization examination data and other predetermined material data.Specifically, skill is acquired with big data Art largely acquires and analyzes the score factor data of the applicant over the years for carrying out school's application.

In addition, the score factor data of passing applicant over the years and the score factor data of present application person are stored in data Library；When needing to call score factor data, the above-mentioned score factor data stored in database is called.

Step S20 wants prime number according to the score of the score factor data, present application person of passing applicant According to determining the synthesized competitiveness standard total score and competitiveness grade of present application person；

It specifically includes：Step S21, according to the score factor data of passing applicant, the meter of present application person Sub-element data, calculate separately passing applicant respectively score element standard scores, present application person each score element standard scores；

Step S22, according to passing applicant respectively score element standard scores, present application person each score element standard scores, Calculate the synthesized competitiveness standard total score of present application person；And the synthesized competitiveness standard according to present application person Total score determines ranking of the present application person in default group；

Table 1

Specifically, according to the synthesized competitiveness standard total score of present application person and be included in calculating applicant it is (passing Applicant adds present application person) sum, ranking of the present application person in passing applicant can be easily obtained, To accurately depict level of competitiveness of the present application person relative to passing applicant.Further, it is also possible to by obtain with Present application person's the same year carries out the most of school's application or all the score factor data of other applicants, and calculates current The synthesized competitiveness standard total score that applicant applies in current year, to obtain ranking of the present application person in current year applicant Situation, and then easily determine level of competitiveness of the present application person relative to current year applicant, the ginseng of current year application is provided Examine information.

Step S23, it is competing according to the synthesized competitiveness standard total score of passing applicant, the synthesis of present application person Power standard total score is striven, determines the competitiveness grade of present application person；

Step S24 determines the level of strength grade of each school according to the score factor data of passing applicant.

Step S30 establishes the application of pre-selection school according to the score factor data of the passing applicant of pre-selection school Winner's model；Wherein, pre-selection school is the school of school or system recommendation that present application person selectes, if passing through pre-selection Gan Ge schools carry out individual application's competitiveness intelligent evaluation of school's application, finally obtain current Shen corresponding with each pre-selection school Please person individual application's Competitiveness Assessment result.

In some specific implementations, each is established according to the score factor data of passing applicant and default modeling algorithm Application winner's model in school；Wherein, the preferred Bayesian Classification Arithmetic of modeling algorithm is preset.I.e. with the passing applicant person of acquisition Score factor data based on, the score factor data of passing applicant is subjected to classification storage, then calculate by data mining Method extracts each of each passing applicant score component attributes and index, to carry out data analysis and modeling.The number Include but not limited to following algorithm according to mining algorithm：Decision tree analysis algorithm, neural network analysis algorithm (neural network Algorithm), cluster algorithm, Association Rule Analysis algorithm, logistic re-gression analysis algorithm (Logistic regression algorithm)。

In some specific implementations, pass through decision tree analysis algorithm owning the school in a certain level of strength grade The correlometer sub-element data (including score component attributes and corresponding achievement data) of passing applicant are analyzed, to Go out all factors to applying for successfully and applying the influence correlation to fail.Then, by cluster algorithm analyze application at Work(person and application loser respectively possessed by peculiar common score factor data (including score component attributes and corresponding index Data).By the above two alanysis result be combined sort and establish several application winner's model, then by application at Randomly drawing sample is sampled in the database of two class people of work(and loser, the accuracy rate of test application winner's model, and Using the highest application winner's model of accuracy rate as carrying out present application person by the application success of admission probabilistic forecasting Person's model.

Step S40, according to the score factor data of present application person and the application winner mould of pre-selection school Type, calculate present application person correspond to pre-selection school by admission probability；

In some specific implementations, based on application winner's model, the score factor data of present application person is transported Calculate, analysis obtain present application person correspond to it is different pre-selection schools by admission probability.

Step S50 determines that present application person corresponds to the Competitiveness strategy of pre-selection school；And generate present application person Analysis report of selecting a school.

It should be noted that since many schools are equipped with student enrollment limit, and many schools for particular country Foreign student also is provided with admission limit.Therefore, only provide present application person correspond to pre-selection school by admission probability, can not be worked as Preceding applicant provides fully comprehensive reference information.The present invention and existing traditional artificial consultation way or on-line consulting system The mode seeked advice from the difference is that, intelligent evaluation system of the invention not only provides intuitive to present application person People's overall ranking and ranking in its residing competitiveness grade, moreover it is possible to be provided to present application person at this by way of brushing and selecting Ranking in state current year applicant.That is, the intelligent evaluation system of the present invention can be based on present application person and other applicants The score element of (including passing applicant and current year applicant) calculates the synthesized competitiveness standard total score P of present application person (ts), competitiveness grade, and ranking of the present application person under all kinds of ranked categories can be further obtained, to make It obtains current applicant and grasps itself abundant and comprehensive level of competitiveness information, to be more advantageous to decision references.Therefore, currently Can also include synthesized competitiveness standard total score P (ts), competitiveness grade and relevant row in the analysis report of selecting a school of applicant Name situation.

In addition, further including that analysis report of selecting a school described in present application person is sent to the user terminal.Active user It is received by user terminal and generates analysis report of selecting a school, to know the competitiveness result of itself, by selected target school Enroll probabilistic information.

In addition, further including realizing to apply operating to the relevant school of present application person.For example, present application person is submitted Application materials carry out preliminary inquiry；And submit the application material of present application person to official's application for enrollment in a school system；And inquiry The application status of present application person.

The present embodiment will apply for that highly relevant key unstructured data and structural data are incorporated into school Score factor data, and largely acquire the score factor data of passing applicant.Score element based on a large amount of passing applicants The quantization of unstructured data in data, and score factor data, accurately analyzes the competitiveness water of present application person Flat and corresponding different level of strength grades school by admission probability, Shen can not be combined by compensating for existing school's application consulting tool Please person unstructured data carry out school application personal analysis on competitive deficiency.Meanwhile it also being provided for present application person Accurately and effectively Competitiveness strategy and convenient intuitively select a school analysis report and solution, to be current Shen Please person provide school's application it is abundant it is intuitive, accurately and effectively personal Competitiveness Assessment information has to carry out decision references Help applicant preferably to make school's application decision and increase application success rate.The embodiment of the present invention realizes one-stop intelligent Online school's application consulting applies for that consulting (such as consultation on the study abroad) needs the face-to-face of height or online and consultant with traditional school Exchange is different, saves the cumbersome flow and high communication cost that applicant exchanges with consultant, and applicant is helped to realize Analysis on competitive on self-service line finds out shortcomings and provides a whole set of lines such as improvement strategy, online application and application result tracking On school application prepare overall process.

Further, the determining present application person corresponds to the step of the Competitiveness strategy of pre-selection school, specific to wrap It includes：

Step S51, by changing the score factor data of present application person, calculate corresponding pre-selection school by admission probability Enhancing rate；It optimal promote score according to by the enhancing rate of admission probability, determine corresponding pre-selection school and wants prime implicant and correspondence Competitiveness strategy.

Further, the determining present application person corresponds to the step of the Competitiveness strategy of pre-selection school, specific to go back Including：

Step S52 wants prime number according to the score of the application winner model of pre-selection school and present application person According to determining that present application person corresponds to the weak score of apply winner's model of pre-selection school and wants prime implicant, and determining corresponding Competitiveness strategy.

In some specific implementations, according to the synthesized competitiveness standard total score of present application person, described competitiveness etc. Grade and described by admission probability, generates the Competitiveness strategy of present application person.For example, comparing the competitiveness of present application person The corresponding synthesized competitiveness total score of grade synthesized competitiveness total score score value interval limit corresponding with more excellent level-one competitiveness grade Value, the score value gap both determined, and the relatively low score element of score of present application person is searched, to generate for current The Competitiveness strategy of the practical competitiveness situation of applicant.For example, the Competitiveness strategy includes：If current Shen Please person extracurricular activities score component scores it is relatively low, then want prime implicant labeled as needing improved score element extracurricular activities score .In other words, present application person obtains the Competitiveness strategy by user terminal, and prime implicant pair is wanted in reply extracurricular activities score The sub- element item of each score answered is promoted and is reinforced, to promote level of competitiveness.Further, to the competitiveness of generation Promotion Strategy carries out performability analysis, if analysis result is the presence of the improvement item being difficult to realize in the competitiveness improvement project Mesh is then labeled to inform present application person the improved project.

In some specific implementations, according to the synthesized competitiveness standard total score of present application person, described competitiveness etc. Grade and it is described by admission probability, determine the level of strength grade of the matched school of the level of competitiveness of present application person；According to true The level of strength grade of fixed school searches the school in the level of strength grade, and generates present application person by the reality The Competitiveness strategy of school's admission of power hierarchical level.And the school for being better than above-mentioned level of strength grade is searched, and By the Competitiveness strategy of corresponding school's admission.

In the present embodiment, by the way that there is constructive and enforceability Competitiveness to applicant's offer multi-angle Strategy to contribute to applicant to understand the competitiveness situation of itself, and is made using the Competitiveness strategy of offer and being directed to Property improvement and promotion activity, contribute to increase applicant application success rate.

Further, as shown in figure 5, the score factor data of the passing applicant according to pre-selection school, builds After the step of application winner's model of vertical pre-selection school, further include：

Step S60 determines competitiveness prediction result based on default test data according to application winner's model, and Obtain the competitiveness result that the competitiveness scoring subsystem is determined based on the default test data；

The competitiveness prediction result is compared by step S61 with the competitiveness result, and according to obtained comparison The accuracy for applying for winner's model described in outcome evaluation, to obtain Accuracy evaluation result；

Step S62, according to the Accuracy evaluation as a result, optimization application winner's model.

After establishing application winner's model, need constantly to assess established application winner's model, to comment The prediction accuracy of model is sentenced, to constantly carry out the optimization of model, to realize best prediction effect.Wherein, to application When winner's model is assessed, the assessment data of selection are prediction test data, are preferably stored in passing in database The score factor data of applicant.For example, the score factor data of several random passing applicants of selection is passed through application Winner's model carries out operation and analysis, and it (includes but not limited to synthesized competitiveness total score and competition to obtain competitiveness prediction result Power grade).Then, the score factor data of several random passing applicants of selection is subjected to operation and analysis, obtained pair The competitiveness result (including but not limited to synthesized competitiveness total score and competitiveness grade) answered.By competitiveness prediction result and competition Power result is compared, and judges the gap of the two；According to the gap judging result of the two, the prediction of application winner's model is judged Accuracy.

It should be noted that herein, the terms "include", "comprise" or its any other variant are intended to non-row His property includes, so that process, method, article or system including a series of elements include not only those elements, and And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including this There is also other identical elements in the process of element, method, article or system.

The embodiments of the present invention are for illustration only, can not represent the quality of embodiment.

Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side Method can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware, but in many cases The former is more preferably embodiment.Based on this understanding, technical scheme of the present invention substantially in other words does the prior art Going out the part of contribution can be expressed in the form of software products.

It these are only the preferred embodiment of the present invention, be not intended to limit the scope of the invention, it is every to utilize this hair Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills Art field, is included within the scope of the present invention.

Claims

1. a kind of personal competitiveness intelligent evaluation system carrying out school's application, including：User terminal, connection network, database, It is characterized in that, further including：Data acquisition subsystem, data modeling and analyzing subsystem, is selected a school point at competitiveness scoring subsystem Analysis and application subsystem；Wherein,

The data acquisition subsystem, the score factor data for acquiring passing applicant, and pass through the connection network It is connect with the user terminal, receives the score factor data for the present application person that the user terminal is sent, and by passing Shen Please the score factor data of person and the score factor data of present application person store to the database；

The competitiveness scores subsystem, for the institute according to the score factor data of passing applicant, present application person Score factor data is stated, determines the synthesized competitiveness standard total score and competitiveness grade of present application person；

The data modeling and analyzing subsystem include modeling module, Success Rate Analysis module；The modeling module is used for basis The score factor data of the passing applicant of school is preselected, application winner's model of pre-selection school is established；The success Rate analysis module, for according to the score factor data of present application person and the application winner mould of pre-selection school Type, calculate present application person correspond to pre-selection school by admission probability；

Select a school analysis and the application subsystem, for determining that present application person corresponds to the Competitiveness strategy of pre-selection school； And generate the analysis report of selecting a school of present application person.

2. carrying out the personal competitiveness intelligent evaluation system of school's application as described in claim 1, which is characterized in that the meter The corresponding score of sub-element data wants the prime implicant to include：Background information, academic aptitude, extracurricular activities, standardization examination and other pre- If material.

3. carrying out the personal competitiveness intelligent evaluation system of school's application as described in claim 1, which is characterized in that described competing It includes the total sub-module of competitiveness, competitiveness grade module to strive power scoring subsystem；Wherein,

The total sub-module of competitiveness is used for described in the score factor data according to passing applicant, present application person Score factor data, calculate separately passing applicant respectively score element standard scores, present application person each score element standard scores； According to passing applicant respectively score element standard scores, present application person each score element standard scores, calculate present application person The synthesized competitiveness standard total score；

And the synthesized competitiveness standard total score according to present application person, determine row of the present application person in default group Name situation；

The competitiveness grade module, for according to the synthesized competitiveness standard total score of passing applicant, present application person The synthesized competitiveness standard total score, determine the competitiveness grade of present application person；And according to passing applicant's The score factor data determines the level of strength grade of each school.

4. carrying out the personal competitiveness intelligent evaluation system of school's application as described in claim 1, which is characterized in that described to select It includes analysis module of selecting a school that school, which is analyzed with application subsystem,；

The analysis module of selecting a school calculates corresponding pre-selection school for the score factor data by changing present application person By the enhancing rate of admission probability；It optimal promote score according to by the enhancing rate of admission probability, determine corresponding pre-selection school and wants Prime implicant and corresponding Competitiveness strategy.

5. carrying out the personal competitiveness intelligent evaluation system of school's application as claimed in claim 4, which is characterized in that described to select School analysis module is additionally operable to want prime number according to the application winner model of pre-selection school and the score of present application person According to determining that present application person corresponds to the weak score of apply winner's model of pre-selection school and wants prime implicant, and determining corresponding Competitiveness strategy.

6. the personal competitiveness intelligent evaluation system for carrying out school's application as described in claim 1,4 or 5 are any, feature exist In, present application person it is described select a school analysis report including at least present application person correspond to pre-selection school by admission probability and/ Or Competitiveness strategy and/or synthesized competitiveness standard total score and/or competitiveness grade.

7. carrying out the personal competitiveness intelligent evaluation system of school's application as described in claim 1, which is characterized in that the number Further include model optimization module according to modeling and analyzing subsystem；Wherein,

The model optimization module, for based on default test data, determining that competitiveness is pre- according to application winner's model It surveys as a result, and obtaining the competitiveness result that the competitiveness scoring subsystem is determined based on the default test data；It will be described Competitiveness prediction result is compared with the competitiveness result, and assesses the application winner according to obtained comparison result The accuracy of model, to obtain Accuracy evaluation result；According to the Accuracy evaluation as a result, optimization application winner's mould Type.

8. a kind of personal competitiveness intelligent evaluation method carrying out school's application, which is characterized in that progress school application Personal competitiveness intelligent evaluation method includes：

It acquires the score factor data of passing applicant, and receives the score factor data of present application person, and by passing Shen Please the score factor data of person and the score factor data of present application person store to database；

According to the score factor data of passing applicant, the score factor data of present application person, current Shen is determined Please person synthesized competitiveness standard total score and competitiveness grade；

According to the score factor data of the passing applicant of pre-selection school, application winner's model of pre-selection school is established；

According to the score factor data of present application person and the application winner model of pre-selection school, current Shen is calculated Please person correspond to pre-selection school by admission probability；

Determine that present application person corresponds to the Competitiveness strategy of pre-selection school；And generate the analysis report of selecting a school of present application person It accuses.

9. carrying out the personal competitiveness intelligent evaluation method of school's application as claimed in claim 8, which is characterized in that described According to the score factor data of passing applicant, the score factor data of present application person, determine present application person's The step of synthesized competitiveness standard total score and competitiveness grade includes：

According to the score factor data of passing applicant, the score factor data of present application person, calculated separately Toward applicant respectively score element standard scores, present application person each score element standard scores；

According to passing applicant respectively score element standard scores, present application person each score element standard scores, calculate present application The synthesized competitiveness standard total score of person；

The synthesized competitiveness standard according to the synthesized competitiveness standard total score of passing applicant, present application person is total Point, determine the competitiveness grade of present application person；

10. carrying out the personal competitiveness intelligent evaluation method of school's application as claimed in claim 8, which is characterized in that described It determines that present application person corresponds to the step of the Competitiveness strategy of pre-selection school, specifically includes：The analysis module of selecting a school is logical The score factor data for changing present application person is crossed, the enhancing rate by admission probability of corresponding pre-selection school is calculated；According to being recorded It takes the enhancing rate of probability, determines that the optimal of corresponding pre-selection school promotes score and want prime implicant and corresponding Competitiveness strategy；

Alternatively, according to the application winner model of pre-selection school and the score factor data of present application person, determine Prime implicant is wanted in the weak score that present application person corresponds to application winner's model of pre-selection school, and determines that corresponding competitiveness carries Rise strategy.