CN110046768A - Method, apparatus and system based on professional ability system prediction college students'employment - Google Patents
Method, apparatus and system based on professional ability system prediction college students'employment Download PDFInfo
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Abstract
The embodiment of the invention discloses a kind of method, apparatus and system based on professional ability system prediction college students'employment, this method comprises: obtaining the school grade of student to be predicted；According to the school grade of student to be predicted, the professional ability degree of reaching of student to be predicted is determined；The professional ability degree of reaching of student to be predicted is input in the Obtained employment orientation prediction model of prebuild, the Obtained employment orientation of student is predicted, and shows prediction result to student to be predicted.By all school grades of the student during school, the postgraduate Obtained employment orientation of each student can be predicted.To for the postgraduate Obtained employment orientation of student provide reference frame, reduce the anxiety before student graduates and vast and hazy.
Description
Technical field
The present embodiments relate to technical field of data processing, and in particular to one kind predicts university based on professional ability system
The method, apparatus and system of Adult Students ' Employment.
Background technique
Continuous with educational undertaking is popularized, and more and more families appreciate the importance of knowledge.Consequent,
Efficient continuous increased enrollment, university student are more and more.But after student's graduation, but face difficult choice.University student is for oneself institute
How this applies professional knowledge, how to select to obtain employment, how are career prospects? whether public institution is prepared for the postgraduate qualifying examination or enters oneself for the examination in consideration
Etc., most of people can be more vast and hazy, does not know that course to follow.
Although some colleges and universities can all count the employment status of this year's graduates every year, such as whole employment rate is how many, student
Substantially Obtained employment orientation which includes.But these are whole for some profession, or entirely this of school is all complete
For industry is raw.This statistical data can not provide the student that will graduate the effect of too big guidance and auxiliary.
So, how its postgraduate Obtained employment orientation could be predicted for each student that will graduate, to subtract as far as possible
Vast and hazy and anxiety before few student's graduation, becomes technical problems to be solved in this application.
Summary of the invention
For this purpose, the embodiment of the present invention provide it is a kind of based on professional ability system prediction college students'employment method, apparatus and
System cannot be apparent from possible Obtained employment orientation after oneself graduating with the university student for solving to graduate in the prior art
Technical problem.
To achieve the goals above, the embodiment of the present invention provides the following technical solutions:
According to a first aspect of the embodiments of the present invention, it provides a kind of based on professional ability system prediction college students'employment
Method, this method comprises: obtaining the school grade of student to be predicted；
According to the school grade of student to be predicted, the professional ability degree of reaching of student to be predicted is determined；
The professional ability degree of reaching of student to be predicted is input in the Obtained employment orientation prediction model of prebuild, to student's
Obtained employment orientation is predicted, and shows prediction result to student to be predicted.
Further, the school grade of student to be predicted includes: each subject that student to be predicted learns during university
The final examination school grade of journey.
Further, according to the school grade of student to be predicted, the professional ability degree of reaching of student to be predicted is determined, specifically
Include:
According to the final examination school grade of every a branch of instruction in school of student to be predicted, commented from pre-established professional ability index
Corresponding evaluation index and corresponding first weighted value of evaluation index are matched in valence system；
According to the final examination school grade of every a branch of instruction in school of student to be predicted, the corresponding evaluation index of every a branch of instruction in school
And corresponding first weighted value of evaluation index, determine the professional ability degree of reaching of student to be predicted.
Further, when evaluation index includes at least one, and each evaluation index includes at least one second level
It is corresponding according to the final examination school grade of every a branch of instruction in school of student to be predicted, every a branch of instruction in school when other subsystem assessment indicator
Evaluation index and corresponding first weighted value of evaluation index, determine the professional ability degree of reaching of student to be predicted, it is specific to wrap
It includes:
In second level, will the second weighted value corresponding with the first subsystem assessment indicator, respectively with first son evaluation refer to
Mark corresponding every a branch of instruction in school final examination school grade do product after, by all product numerical value be superimposed, as second level
In the first total performance corresponding with the first subsystem assessment indicator；
It will average after the corresponding total performance superposition of each of second level subsystem assessment indicator, as with first
Corresponding second total performance of rank；
According to corresponding second total performance of first level, the professional ability degree of reaching of student to be predicted is determined, wherein the
One subsystem assessment indicator is any one subsystem assessment indicator in second level at least one subsystem assessment indicator.
Further, before the school grade for obtaining student to be predicted, method further include:
Obtain the employment side of each student in the school grade and all previous students of all previous students in preset time period
To label；
According to the school grade of each student in all previous students, the professional ability of each student in all previous students is determined
Degree of reaching；
Just according to each student in the professional ability degree of reaching of each student in all previous students and all previous students
Industry direction label is trained BP neural network model, determines optimal training pattern, for the Obtained employment orientation as prebuild
Prediction model.
Further, the professional ability degree of reaching of student to be predicted is input to the Obtained employment orientation prediction model of prebuild
In, the Obtained employment orientation of student is predicted, and show prediction result to before student to be predicted, method further include:
Obtain student's school information and specialized information；
The Obtained employment orientation of prebuild corresponding with student's school information and specialized information is matched from pre-established database
Prediction model.
According to a second aspect of the embodiments of the present invention, it provides a kind of based on professional ability system prediction college students'employment
Device, the device include:
Device includes:
Acquiring unit, for obtaining the school grade of student to be predicted；
Processing unit determines the professional ability degree of reaching of student to be predicted for the school grade according to student to be predicted；
Predicting unit, the Obtained employment orientation for the professional ability degree of reaching of student to be predicted to be input to prebuild predict mould
In type, the Obtained employment orientation of student is predicted；
Display unit, for showing prediction result to student to be predicted.
Further, the school grade of student to be predicted includes: each subject that student to be predicted learns during university
The final examination school grade of journey, processing unit are specifically used for:
According to the final examination school grade of every a branch of instruction in school of student to be predicted, commented from pre-established professional ability index
Corresponding evaluation index and corresponding first weighted value of evaluation index are matched in valence system；
According to the final examination school grade of every a branch of instruction in school of student to be predicted, the corresponding evaluation index of every a branch of instruction in school
And corresponding first weighted value of evaluation index, determine the professional ability degree of reaching of student to be predicted.
Further, device further include: training unit；
Acquiring unit is also used to, and is obtained each in the school grade and all previous students of all previous students in preset time period
The Obtained employment orientation label of position student；
Processing unit is also used to, and according to the school grade of each student in all previous students, is determined each in all previous students
The professional ability degree of reaching of position student；
Training unit, for according to every in the professional ability degree of reaching of each student in all previous students and all previous students
The Obtained employment orientation label of one student, is trained BP neural network model, determines optimal training pattern, for being used as pre- structure
The Obtained employment orientation prediction model built.
According to a third aspect of the embodiments of the present invention, it provides a kind of based on professional ability system prediction college students'employment
System, the system include: processor and memory；
Memory is for storing one or more program instructions；
Processor, it is as above a kind of pre- based on professional ability system for executing for running one or more program instructions
Method step either in the method for survey college students'employment；
Display, for showing the prediction result to the student to be predicted.
According to a fourth aspect of the embodiments of the present invention, a kind of computer storage medium is provided, the computer storage medium
In comprising one or more program instructions, one or more program instructions are used to predict university based on professional ability system by one kind
The system of Adult Students ' Employment either executes in a kind of as above method based on professional ability system prediction college students'employment method step.
The embodiment of the present invention has the advantages that the school grade for obtaining student to be predicted, according to student to be predicted
Achievement is practised, determines the professional ability degree of reaching of student to be predicted.Then the professional ability degree of reaching of student to be predicted is input to
In the Obtained employment orientation prediction model of prebuild, the Obtained employment orientation of student is predicted, obtain prediction result and is showed to pre-
Survey student.By all school grades of the student during school, the postgraduate Obtained employment orientation of each student can be predicted.From
And reference frame is provided for the postgraduate Obtained employment orientation of student, the anxiety and vast and hazy before reducing student's graduation.
Detailed description of the invention
It, below will be to embodiment party in order to illustrate more clearly of embodiments of the present invention or technical solution in the prior art
Formula or attached drawing needed to be used in the description of the prior art are briefly described.It should be evident that the accompanying drawings in the following description is only
It is merely exemplary, it for those of ordinary skill in the art, without creative efforts, can also basis
The attached drawing of offer, which is extended, obtains other implementation attached drawings.
Structure depicted in this specification, ratio, size etc. are only used for the cooperation revealed content of specification, for
Those skilled in the art understands and reads, and is not intended to limit the enforceable qualifications of the present invention, therefore does not have technical
Essential meaning, the modification of any structure, the change of proportionate relationship or the adjustment of size are not influencing the function of the invention that can be generated
Under effect and the purpose that can reach, should all still it fall in the range of disclosed technology contents obtain and can cover.
Fig. 1 is a kind of method flow that college students'employment is predicted based on professional ability system that the embodiment of the present invention 1 provides
Schematic diagram；
Fig. 2 is a kind of apparatus structure that college students'employment is predicted based on professional ability system that the embodiment of the present invention 2 provides
Schematic diagram；
Fig. 3 is a kind of system structure that college students'employment is predicted based on professional ability system that the embodiment of the present invention 3 provides
Schematic diagram.
Specific embodiment
Embodiments of the present invention are illustrated by particular specific embodiment below, those skilled in the art can be by this explanation
Content disclosed by book is understood other advantages and efficacy of the present invention easily, it is clear that described embodiment is the present invention one
Section Example, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not doing
Every other embodiment obtained under the premise of creative work out, shall fall within the protection scope of the present invention.
The embodiment of the present invention 1 provides a kind of method based on professional ability system prediction college students'employment, specific such as Fig. 1
Shown, the student that this method is mainly used in the same profession of same school predicts, the student of different majors, needs to construct not
Same Obtained employment orientation prediction model.The method steps are as follows:
Step 110, the school grade of student to be predicted is obtained.
Specifically, the school grade of student to be predicted can fill in upload by student itself, or defeated in systems
Enter the identification informations such as student number, then transfers the school grade of student from background data base by system itself.
Optionally, the school grade of student include all courses of the student university during school final examination study at
Achievement.If certain a branch of instruction in school is only wherein taken an examination, without final examination, then can using its wherein total marks of the examination as final
Total marks of the examination are called.And including the achievements such as student's make-up examination, reconditioning do not cover, it does not consider.
Step 120, according to the school grade of student to be predicted, the professional ability degree of reaching of student to be predicted is determined.
Specifically, can be according to the final examination achievement of every a branch of instruction in school of student to be predicted, from pre-established professional energy
Corresponding evaluation index and corresponding first weighted value of evaluation index are matched in power indicator evaluation system.Then, according to
Final examination school grade, the corresponding evaluation index of every a branch of instruction in school and the evaluation index of every a branch of instruction in school of student to be predicted
Corresponding first weighted value determines the professional ability degree of reaching of student to be predicted.
Here it is special that professional ability indicator evaluation system mainly carries out personnel training according to the gone up course of each student
Industry ability is sorted out, and sets an indicator evaluation system of corresponding degree of reaching.
In a specific example, such as the software engineering speciality of certain colleges and universities, professional ability indicator evaluation system can
To include requiring 1-12, requirements for graduation 1: the required mathematics of this profession, natural science, Computer Subject basis and software work are grasped
Journey professional knowledge can be used to solve the complex software engineering problem in embedded/mobile Internet application software field.Requirements for graduation
2: can applied mathematics, the basic principle of natural science and soft project, identification, express simultaneously by literature research analysis insertion
Formula/mobile Internet application software field complex software engineering problem, to obtain valid conclusion.Requirements for graduation 3: it can design
For the solution of embedded software/mobile Internet application software field complex software engineering problem, design meets special
Determine the software systems or software module of demand, and creativity consciousness can be embodied in design link, consider society, health, safety,
The factors such as law, culture and environment.Requirements for graduation 4: can based on the principles of science and using scientific method to embedded software/
The complex software engineering problem in mobile Internet application software field is studied, including contrived experiment, analysis and explanation data,
And reasonable effective conclusion is obtained by informix.Requirements for graduation 5: embedded software/mobile Internet application can be directed to
The complex software engineering problem of software field, exploitation select and use appropriate technology, resource, modern project tool and information
Technical tool, including the prediction and simulation to complex software engineering problem, and it will be appreciated that its limitation.Requirements for graduation 6: can
Reasonable analysis, the practice of evaluation specialized engineering and complex software engineering problem solution party are carried out based on soft project relevant background knowledge
Influence of the case to society, health, safety, law and culture, and understand the responsibility that should bear.Requirements for graduation 7: it will be appreciated that and
Evaluation is practiced for the specialized engineering of embedded software/mobile Internet application software field complex software engineering problem to ring
The influence in border, social sustainable development.Requirements for graduation 8: having humanity social sciences attainment and social responsibility, understands with this specially
The relevant important law of industry, regulation and policy and policy abide by engineering professional ethics and specification in practice, fulfil responsibility.Finish
Industry requires 9: individual, Team Member and the role of responsible person can be undertaken in the team under multidisciplinary background.Requirements for graduation
10: can go together with regard to embedded software/mobile Internet application software field complex software engineering problem and industry and social
The public carry out effective communication with exchange, including write report and design manuscript, statement speech, clear expression or respond instruction.And
Have certain international vision, can be linked up and be exchanged under cross-cultural background.Requirements for graduation 11: understanding and grasps engineering
Principle and economic decision-making method are managed, and can be applied in multidisciplinary environment.Requirements for graduation 12: there is autonomous learning and lifelong
The consciousness of habit has constantly study and adapts to the ability of development.
It is setting number when it reaches requirement it is possible to set each requirements for graduation as a level-one evaluation index
Value is 1, is otherwise 0.Each of which requirements for graduation can set first weighted value, such as first requirements for graduation is corresponding
Weighted value is 0.1, and second requirements for graduation can be set to 0.08 etc., in short, if it is 12 requirements for graduation, weighted value is total
Be 1, how much specific setting can be manually set according to the actual situation, for example, the weighted value of each requirements for graduation is 1/
12 is also possible.Here excessive explanation is not done.Then, when each requirements for graduation reaches, then corresponding weighted value is obtained, i.e.,
Otherwise first weighted value loses corresponding weighted value.Here reach requirements for graduation, it is also necessary to be determined according to course,
Each requirements for graduation will be for one or more subjects, if it is assumed that the weight of each requirements for graduation
Ratio is 100%, and the corresponding course number of the requirements for graduation includes 4, and each proportion is 25%, then, each subject
The final grade of journey, multiplied by weighted value shared by the requirements for graduation, obtains a numerical value multiplied by corresponding ratio.If it is 4
This 4 numerical value superpositions will just be obtained the professional ability degree of reaching of the requirements for graduation by course, inevitable available 4 numerical value.
Finally calculate corresponding professional ability degree of the reaching summation of all requirements for graduation, the professional energy as final student to be predicted
Power degree of reaching.
It is further alternative, in order to enable the professional ability degree of reaching of student to be predicted is more accurate.It can also be right respectively
Each level-one evaluation index is finely divided, and is subdivided into multiple second level subsystem assessment indicators, or, further segment, it will
Each second level subsystem assessment indicator is further subdivided into multiple three-level indexs etc..Specifically it may be set according to actual conditions.?
In specific example above, level-one evaluation index multiple second level subsystem assessment indicators, such as requirements for graduation 1 have been further subdivided into
4 second level subsystem assessment indicators are subdivided into, as shown in table 1.
Table 1
As can be seen that the weighted value summation of each second level subsystem assessment indicator is 1 in table 1, for every a branch of instruction in school in table 1,
Respectively correspond the weighted value of second level subsystem assessment indicator, i.e. the second weighted value.Do not have data in table is then defaulted as 0.So,
Can will the second weighted value corresponding with the first subsystem assessment indicator, respectively and every a branch of instruction in school corresponding with the first subsystem assessment indicator
Final examination school grade do product after, by all product numerical value be superimposed, as in second level with the first subsystem assessment indicator
Corresponding first total performance；
It will average after the corresponding total performance superposition of each of second level subsystem assessment indicator, as with first
Corresponding second total performance of rank；
According to corresponding second total performance of first level, the professional ability degree of reaching of student to be predicted is determined, wherein the
One subsystem assessment indicator is any one subsystem assessment indicator in second level at least one subsystem assessment indicator.
Specifically, second level in such as table 1, that is to say include in second level subsystem assessment indicator 1.1, understand mathematics, from
So relevant knowledge and basic principle of science.Its corresponding course has corresponding second weighted value, comprising: high data (A1-
A2), 0.3；Linear algebra, 0.2；Probability Theory and Math Statistics, 0.2, College Physics (C1-C2), 0.1；Discrete mathematics, 0.2.Its
His weighted value is that 0 can ignore.It may include high data final examination achievement multiplied by power when calculating the first total performance
0.3 is weighed, in addition linear algebra final examination achievement is multiplied by 0.2, in addition College Physics final examination achievement is added multiplied by 0.1
Discrete mathematics final examination achievement is multiplied by the numerical value after 0.2.Using similar method, calculate two-level index 1.2,1.3 and
Corresponding first total performances such as 1.4.To average after this 4 first total performances superposition, as first it is comprehensive at
Achievement that is to say the professional ability degree of reaching of requirements for graduation 1.Similar fashion, the professional ability for calculating requirements for graduation 2-12 are reached
Degree, finally, seeks the average value of this 12 professional ability degree of reaching, the final professional ability as student to be predicted is reached
Degree.
As follows, table 2 also lists out the corresponding two-level index of requirements for graduation 2 and corresponding course is corresponding
Weighted value.Only list corresponding contents corresponding to requirements for graduation 1 and requirements for graduation 2 in the present embodiment, it is other with it is such
Seemingly, level-one standard diagrams, second level subsystem assessment indicator and corresponding course, corresponding weight etc. are determines according to actual conditions
, so more explanations are not listed.
Table 2
Step 130, the professional ability degree of reaching of student to be predicted is input in the Obtained employment orientation prediction model of prebuild,
The Obtained employment orientation of student is predicted, and shows prediction result to student to be predicted.
Optionally, before executing step 130, this method can also include:
Obtain the employment side of each student in the school grade and all previous students of all previous students in preset time period
To label；
According to the school grade of each student in all previous students, the professional ability of each student in all previous students is determined
Degree of reaching；
Just according to each student in the professional ability degree of reaching of each student in all previous students and all previous students
Industry direction label is trained BP neural network model, determines optimal training pattern, for the Obtained employment orientation as prebuild
Prediction model.
Specifically, for example obtaining the school grade of 5 graduate students before this profession of colleges and universities.It is of course also possible to more, tool
Body here without limitation, data are more, and natural model is also just more accurate.But data volume is also just bigger, so in this implementation
Done compromise processing, choose from the current term to pervious preceding 5 students of graduate students data as sample data.
According to the method for similar step 120, the professional ability degree of reaching of each student in all previous students is obtained.Then,
The Obtained employment orientation label of each student in all previous students is obtained again.Actually first obtain each student in all previous students
Obtained employment orientation, such as into a certain more famous enterprise, enter government department, or prepare for the postgraduate qualifying examination etc..It is possible to be
Their Obtained employment orientation sets corresponding label: such as enterprise of good standing, public institution, government, prepare for the postgraduate qualifying examination, general unit or other
Etc. a few class Obtained employment orientation labels.
Finally, then the standard of student is had the ability into degree of reaching and Obtained employment orientation label is input to BP neural network model and carries out
Training, determines optimal training pattern, for the Obtained employment orientation prediction model as prebuild.
It is further alternative, due to each Obtained employment orientation prediction model, be all some corresponding school some specially
Industry.Therefore, before executing step 130, this method can also include:
Student's school information and specialized information are obtained, matching and student's school information and profession from pre-established database
The Obtained employment orientation prediction model of the corresponding prebuild of information.
A kind of method based on professional ability system prediction college students'employment provided in an embodiment of the present invention, obtains to be predicted
The school grade of student determines the professional ability degree of reaching of student to be predicted according to the school grade of student to be predicted.Then will
The professional ability degree of reaching of student to be predicted is input in the Obtained employment orientation prediction model of prebuild, to the Obtained employment orientation of student into
Row prediction obtains prediction result and shows student to be predicted.By all school grades of the student during school, can predict
The postgraduate Obtained employment orientation of each student out.To provide reference frame for the postgraduate Obtained employment orientation of student, reduce
Anxiety before raw graduation and vast and hazy.
Corresponding with above-described embodiment 1, the embodiment of the present invention 2 additionally provides a kind of based on professional ability system prediction university
The device of Adult Students ' Employment, it is specific as shown in Fig. 2, the device include: acquiring unit 201, processing unit 202, predicting unit 203 and
Display unit 204.
Acquiring unit 201, for obtaining the school grade of student to be predicted；
Processing unit 202 determines that the professional ability of student to be predicted is reached for the school grade according to student to be predicted
Degree；
Predicting unit 203, the Obtained employment orientation for the professional ability degree of reaching of student to be predicted to be input to prebuild are pre-
It surveys in model, the Obtained employment orientation of student is predicted；
Display unit 204, for showing prediction result to student to be predicted.
Optionally, the school grade of student to be predicted includes: every a branch of instruction in school that student to be predicted learns during university
Final examination school grade.
Optionally, processing unit 202, specifically for according to the final examination study of every a branch of instruction in school of student to be predicted at
Achievement matches corresponding evaluation index and evaluation index corresponding from pre-established professional ability indicator evaluation system
One weighted value；
According to the final examination school grade of every a branch of instruction in school of student to be predicted, the corresponding evaluation index of every a branch of instruction in school
And corresponding first weighted value of evaluation index, determine the professional ability degree of reaching of student to be predicted.
Optionally, when evaluation index includes at least one, and each evaluation index includes at least one second level
Subsystem assessment indicator when, processing unit 202 is specifically used for, will corresponding with the first subsystem assessment indicator second in second level
Weighted value, respectively and after the final examination school grade of every a branch of instruction in school corresponding with the first subsystem assessment indicator does product, by institute
There is the superposition of product numerical value, as the first total performance corresponding with the first subsystem assessment indicator in second level；
It will average after the corresponding total performance superposition of each of second level subsystem assessment indicator, as with first
Corresponding second total performance of rank；
According to corresponding second total performance of first level, the professional ability degree of reaching of student to be predicted is determined, wherein the
One subsystem assessment indicator is any one subsystem assessment indicator in second level at least one subsystem assessment indicator.
Optionally, acquiring unit 201 is also used to, and obtains the school grade of all previous students in preset time period and all previous
The Obtained employment orientation label of each student in student；
Processing unit 202 is also used to, and according to the school grade of each student in all previous students, is determined every in all previous students
The professional ability degree of reaching of one student；
Just according to each student in the professional ability degree of reaching of each student in all previous students and all previous students
Industry direction label is trained BP neural network model, determines optimal training pattern, for the Obtained employment orientation as prebuild
Prediction model.
Optionally, acquiring unit 201 is also used to, and obtains student's school information and specialized information；
Processing unit 202 is also used to, and is matched from pre-established database corresponding with student's school information and specialized information
Prebuild Obtained employment orientation prediction model.
Each component institute in a kind of device based on professional ability system prediction college students'employment provided in an embodiment of the present invention
The function of execution has been discussed in detail in above-described embodiment 1, therefore does not do excessively repeat here.
A kind of device based on professional ability system prediction college students'employment provided in an embodiment of the present invention, obtains to be predicted
The school grade of student determines the professional ability degree of reaching of student to be predicted according to the school grade of student to be predicted.Then will
The professional ability degree of reaching of student to be predicted is input in the Obtained employment orientation prediction model of prebuild, to the Obtained employment orientation of student into
Row prediction obtains prediction result and shows student to be predicted.By all school grades of the student during school, can predict
The postgraduate Obtained employment orientation of each student out.To provide reference frame for the postgraduate Obtained employment orientation of student, reduce
Anxiety before raw graduation and vast and hazy.
Corresponding with above-described embodiment, the embodiment of the present invention 3 additionally provides a kind of big based on the prediction of professional ability system
The system of Students ' Employment, specifically as shown in figure 3, the system includes: processor 301, memory 302 and display 303；
Memory 302 is for storing one or more program instructions；
Processor 301, for running one or more program instructions, a kind of base for being introduced for executing embodiment as above
The method step either in the method for professional ability system prediction college students'employment；
Display 303, for showing prediction result to student to be predicted.
A kind of system based on professional ability system prediction college students'employment provided in an embodiment of the present invention, obtains to be predicted
The school grade of student determines the professional ability degree of reaching of student to be predicted according to the school grade of student to be predicted.Then will
The professional ability degree of reaching of student to be predicted is input in the Obtained employment orientation prediction model of prebuild, to the Obtained employment orientation of student into
Row prediction obtains prediction result and shows student to be predicted.By all school grades of the student during school, can predict
The postgraduate Obtained employment orientation of each student out.To provide reference frame for the postgraduate Obtained employment orientation of student, reduce
Anxiety before raw graduation and vast and hazy.
Corresponding with above-described embodiment, the embodiment of the invention also provides a kind of computer storage medium, the computers
Include one or more program instructions in storage medium.Wherein, one or more program instructions are used for by one kind based on professional energy
The system of power system prediction college students'employment executes one kind as described above and is based on professional ability system prediction college students'employment
Method.
Although above having used general explanation and specific embodiment, the present invention is described in detail, at this
On the basis of invention, it can be made some modifications or improvements, this will be apparent to those skilled in the art.Therefore,
These modifications or improvements without departing from theon the basis of the spirit of the present invention are fallen within the scope of the claimed invention.
Claims (10)
1. a kind of method based on professional ability system prediction college students'employment, which is characterized in that the described method includes:
Obtain the school grade of student to be predicted；
According to the school grade of the student to be predicted, the professional ability degree of reaching of the student to be predicted is determined；
The professional ability degree of reaching of the student to be predicted is input in the Obtained employment orientation prediction model of prebuild, to
Raw Obtained employment orientation is predicted, and shows the prediction result to the student to be predicted.
2. the method according to claim 1, wherein the school grade of the student to be predicted include: it is described to
The final examination school grade for every a branch of instruction in school that prediction student learns during university.
3. according to the method described in claim 2, it is characterized in that, the school grade according to the student to be predicted, really
The professional ability degree of reaching of the fixed student to be predicted, specifically includes:
According to the final examination school grade of every a branch of instruction in school of the student to be predicted, commented from pre-established professional ability index
Corresponding evaluation index and corresponding first weighted value of the evaluation index are matched in valence system；
According to the final examination school grade of every a branch of instruction in school of the student to be predicted, the corresponding evaluation index of every a branch of instruction in school
And corresponding first weighted value of evaluation index, determine the professional ability degree of reaching of the student to be predicted.
4. according to the method described in claim 3, it is characterized in that, every a branch of instruction in school according to the student to be predicted
Final examination school grade, the corresponding evaluation index of every a branch of instruction in school and corresponding first weighted value of evaluation index, determine institute
Stating student to be predicted to work as the evaluation index includes at least one, and each evaluation index includes at least one second level
Subsystem assessment indicator when, professional ability degree of reaching, specifically include:
In second level, will the second weighted value corresponding with the first subsystem assessment indicator, respectively with the first subsystem assessment indicator pair
After the final examination school grade for the every a branch of instruction in school answered does product, all product numerical value are superimposed, as the second level
In the first total performance corresponding with first subsystem assessment indicator；
It will average after the corresponding total performance superposition of each of second level subsystem assessment indicator, as with first
Corresponding second total performance of rank；
According to corresponding second total performance of first level, the professional ability degree of reaching of the student to be predicted is determined, wherein institute
Stating the first subsystem assessment indicator is any one subsystem assessment indicator in the second level at least one subsystem assessment indicator.
5. according to claim 1 or 2 or 4 described in any item methods, which is characterized in that the study for obtaining student to be predicted
Before achievement, the method also includes:
Obtain the employment side of each student in the school grade and all previous students of all previous students in preset time period
To label；
According to the school grade of each student in all previous students, the profession of each student in all previous students is determined
Ability degree of reaching；
According to each student in the professional ability degree of reaching of each student in all previous students and all previous students
Obtained employment orientation label, BP neural network model is trained, determines optimal training pattern, for as the prebuild
Obtained employment orientation prediction model.
6. according to claim 1 or 2 or 4 described in any item methods, which is characterized in that described by the special of the student to be predicted
Industry ability degree of reaching is input in the Obtained employment orientation prediction model of prebuild, is predicted the Obtained employment orientation of the student, and
Before showing the prediction result to the student to be predicted, the method also includes:
Obtain student's school information and specialized information；
The Obtained employment orientation of prebuild corresponding with student's school information and specialized information is matched from pre-established database
Prediction model.
7. a kind of device based on professional ability system prediction college students'employment, which is characterized in that described device includes:
Acquiring unit, for obtaining the school grade of student to be predicted；
Processing unit determines that the professional ability of the student to be predicted reaches for the school grade according to the student to be predicted
Cheng Du；
Predicting unit, the Obtained employment orientation for the professional ability degree of reaching of the student to be predicted to be input to prebuild predict mould
In type, the Obtained employment orientation of the student is predicted；
Display unit, for showing the prediction result to the student to be predicted.
8. device according to claim 7, which is characterized in that the school grade of the student to be predicted include: it is described to
The final examination school grade for every a branch of instruction in school that prediction student learns during university, the processing unit are specifically used for:
According to the final examination school grade of every a branch of instruction in school of the student to be predicted, commented from pre-established professional ability index
Corresponding evaluation index and corresponding first weighted value of the evaluation index are matched in valence system；
According to the final examination school grade of every a branch of instruction in school of the student to be predicted, the corresponding evaluation index of every a branch of instruction in school
And corresponding first weighted value of evaluation index, determine the professional ability degree of reaching of the student to be predicted.
9. a kind of system based on professional ability system prediction college students'employment, which is characterized in that the system comprises: processor
And memory；
The memory is for storing one or more program instructions；
The processor, for running one or more program instructions, for executing side as claimed in any one of claims 1 to 6
Method；
Display, for showing the prediction result to the student to be predicted.
10. a kind of computer storage medium, which is characterized in that refer in the computer storage medium comprising one or more programs
It enables, one or more of program instructions are used to be executed such as by a kind of system based on professional ability system prediction college students'employment
Method described in any one of claims 1-6.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110517171A (en) * | 2019-08-26 | 2019-11-29 | 成都市知用科技有限公司 | A kind of intelligent platform of cultivating talent of the precision based on Intelligent campus |
| CN110689222A (en) * | 2019-08-20 | 2020-01-14 | 天津理工大学 | Method and device for dynamically evaluating achievement degree of graduation requirement |
| CN113642804A (en) * | 2021-08-27 | 2021-11-12 | 西安交通大学 | Multi-component enhanced family graduate-going prediction and recommendation multitasking method and system |
-
2019
- 2019-04-22 CN CN201910325058.6A patent/CN110046768A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110689222A (en) * | 2019-08-20 | 2020-01-14 | 天津理工大学 | Method and device for dynamically evaluating achievement degree of graduation requirement |
| CN110517171A (en) * | 2019-08-26 | 2019-11-29 | 成都市知用科技有限公司 | A kind of intelligent platform of cultivating talent of the precision based on Intelligent campus |
| CN113642804A (en) * | 2021-08-27 | 2021-11-12 | 西安交通大学 | Multi-component enhanced family graduate-going prediction and recommendation multitasking method and system |
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Application publication date: 20190723 |