CN115238166A - Auxiliary system for student branch departments based on cloud computing - Google Patents
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Abstract
The invention belongs to the field of high and medium schools, relates to a cloud computing analysis technology, and is used for solving the problem that the conventional branch decision system cannot perform branch recommendation on high and medium students without clear targets, in particular to a cloud computing-based auxiliary system for the branch of the students, wherein a cloud analysis platform is in communication connection with an institution analysis module, a professional analysis module and a template analysis module, the institution analysis module is used for performing intentional institution analysis on students intending to the institution and obtaining institution coefficients, and the professional analysis module is used for performing professional analysis on students intending to perform the professional analysis on the institution and obtaining employment coefficients and examination coefficients of intention specialties; according to the invention, template matching is carried out on students without intention colleges and universities and intention specialties through a template analysis module, a development coefficient is calculated through development data after reference object university graduate, and the students select interested industries to carry out template matching.
Description
Technical Field
The invention belongs to the field of high school subjects, relates to a cloud computing analysis technology, and particularly relates to a student subject auxiliary system based on cloud computing.
Background
The invention patent with the publication number of CN112348727A discloses a high school student branch auxiliary decision system, which reduces the blindness of branch selection, better meets the individual learning and growth requirements, and effectively solves the technical problems that the blindness is large and the individual growth requirements are difficult to meet in the high school branch selection in the prior art;
however, the high school student branch decision-making system is limited to only high school students with definite targets for the crowd, and in reality, a great number of high school students inevitably have their own advantages and interests unclear during branch classification, and meanwhile, no definite target colleges and professions exist, so that branch recommendation cannot be completed for the high school students through the existing high school branch decision-making system;
therefore, the auxiliary system for the student department based on the cloud computing is provided.
Disclosure of Invention
The invention aims to provide a cloud computing-based student branch auxiliary system, which is characterized in that a student with an intention institution is subjected to institution analysis through an institution analysis module, the admission condition and the graduation condition of the next year of the intention institution are analyzed, the examination reporting difficulty, the learning difficulty and the graduation difficulty of the intention institution are comprehensively analyzed to obtain an institution coefficient, and the student can know the overall learning difficulty of the institution through the institution coefficient and then consider whether to replace the intention institution; the students can select whether to change the intention specialties or not according to the employment coefficient and the investigation coefficient, and meanwhile, when the students select not to change the intention specialties but change the intention colleges, the students can consider the alternative colleges preferentially, the students can fully know the overall conditions of competition, reading and employment of the intention colleges and the intention specialties before selecting the subject, and the students can make the optimized selection conveniently after self-balancing.
The purpose of the invention can be realized by the following technical scheme:
a student branch auxiliary system based on cloud computing comprises a cloud analysis platform, wherein the cloud analysis platform is in communication connection with a college analysis module, a professional analysis module and a template analysis module;
the institution analysis module is used for carrying out intention institution analysis on students intending to pass to institutions and obtaining institution coefficients, the institution analysis module sends the institution coefficients to mobile phone terminals of the students, and the students select whether to change the intention institutions or not after receiving the institution coefficients;
if the student changes the intention college, performing the intention college analysis again;
if the student does not change the intention colleges, screening alternative colleges for the student;
the professional analysis module is used for performing professional analysis on students who complete the analysis of colleges and universities and obtaining employment coefficients and investigation coefficients of intention specialties, the professional analysis module sends the employment coefficients and the investigation coefficients of the marked objects to mobile phone terminals of the students, and the students select whether to replace the intention specialties after receiving the employment coefficients and the investigation coefficients;
the template analysis module is used for carrying out template analysis on students without intention colleges: the method comprises the steps of marking students without intention colleges as recommended objects, obtaining grade city ranking of the recommended objects in a high school advanced exam and marking the grade city ranking as standard ranking, marking the ranking of L1 before and after the standard ranking as a minimum standard and a maximum standard respectively, wherein L1 is a preset quantity constant, forming a standard range by the minimum standard and the maximum standard, marking all students with ranking within the standard range in the high school advanced exam of the grade city where the recommended objects in the years M1-M2 are positioned as reference objects, wherein the M1 and the M2 are both preset years, and M2 is larger than M1.
Further, the acquisition process of the coefficients of the institution comprises the following steps: the method comprises the steps that students intending to universities are marked as choosers, the students input intention universities into an intention universities and colleges through mobile phone terminals, the intention universities and colleges are marked as intention objects after the intention universities and colleges are received by the intention universities and colleges, and the admission data, graduation data and 32900government data of the intention objects in the last three years are obtained;
summing the recorded data of the last three years and taking the average number to obtain a recorded analysis value LQ; summing graduation data of the last three years and taking the average number to obtain a graduation analysis value BY; the method comprises the following steps of summing up the \32900capitaldata of the last three years and obtaining an average number to obtain an \32900capitalanalysis value YY;
the college coefficient YX is obtained BY the formula YX = (α 1 × LQ + α 2 × BY)/(α 3 × YY), where α 1, α 2, and α 3 are proportionality coefficients, and α 3 > α 2 > α 1 > 0.
Further, the admission data is the ratio of the number of persons admitted to the student in the level city of the student by the intention colleges to the total number of persons admitted to the intention objects; the graduation data is the ratio of the number of graduates of the intention colleges to the total number of students of the corresponding student years; 32900The trade data is the ratio of the number of people who finish closing or returning to school during the period of reading to the total number of people who enter the school in the year of entering the school.
Further, the screening process of the alternative institution comprises the following steps: acquiring institution thresholds YXmin and YXmax of institutions through formulas YXmin = a1 XYX and YXmax = a2 XYX, wherein YXmin is a minimum institution threshold, YXmax is a maximum institution threshold, the institution thresholds YXmin and YXmax form a screening range, acquiring institution coefficients of all universities in grade city of the institution to which the institution is located, and marking the universities with the institution coefficients within the screening range as alternative universities.
Further, the acquiring process of the employment coefficient comprises the following steps: the students input intention specialities to the professional analysis module through the mobile phone terminal, the professional analysis module marks the intention specialities as marked objects after receiving the intention specialities, and employment data of graduates of the marked objects in the last three years are obtained;
the employment data of graduates with the graduation age within one year is the difference SC between the time of employment of the graduates and the time of leaving and leaving, and the unit is month;
the employment data of graduates with the graduation age of one to two years is a ratio ZH of the number of graduate transfer lines to the total number of graduates in the same marked object;
employment data of graduates with the graduation years of two to three years is annual income SR of the graduates, and the unit is ten thousand yuan;
by the formula
Obtaining an employment coefficient JY, wherein beta 1, beta 2 and beta 3 are proportional coefficients, beta 3 is more than beta 2 and more than beta 1 is more than 1, k is a correction factor, and the value of k is 2.34.
Further, the process of acquiring the investigation coefficient comprises: marking the total number of the research students in the last three years of the marked object as BY, marking the total number of the research students reporting and examining the marked object in the last three years as BK, and marking the total number of the research students who pass the examination of the marked object in the last three years as TG; an investigation coefficient KY of the labeling object is obtained BY a formula KY = (γ 1 × BY + γ 2 × TG)/(γ 3 × BK), where γ 1, γ 2, and γ 3 are proportionality coefficients, and γ 1 > γ 2 > γ 3 > 1.
Further, the process that the students receive the employment coefficients and the examination coefficients to professionally select comprises the following steps:
if the student selects to change the intention specialty, whether the student selects to change the intention colleges is confirmed again through the college and universities analysis module:
if the student selects to replace the intention colleges, the college analysis module sends the alternative colleges to the mobile phone terminal of the student, and the student selects the intention colleges from the alternative colleges or re-inputs the intention colleges;
if the students choose not to change the intention colleges, professional screening is carried out in the intention colleges until the students choose not to change the intention specialties after professional analysis;
if the students choose not to change the intention speciality, acquiring the examination reporting data of the marked object, sending the examination reporting data of the marked object to mobile phone terminals of the students by the speciality analysis module, and after receiving the examination reporting data of the marked object, the students choose subjects according to examination reporting requirements of the marked object, wherein the examination reporting data of the marked object is subject requirements of the corresponding speciality on the examination reporting students.
Further, the template recommendation model screens out a template of a recommended object from the reference objects and recommends: acquiring the graduation year of a reference object and marking the graduation year as BN, acquiring the current annual income of the reference object and marking the annual income as NS, acquiring the number of managers at the position of the reference object and marking the number of the managers as GL, and acquiring the development coefficient of the managers by a formula FZ = u x (theta 1 x NS/BN + theta 2 x GL), wherein theta 1, theta 2 and u are proportionality coefficients, and theta 1 is more than theta 2 and more than 1;
the method comprises the steps of classifying reference objects according to industries where the reference objects are located and generating keywords, selecting the industries by the recommended objects through the selected keywords, marking the selected industries as selected industries, marking three reference objects with the highest development coefficients in the selected industries as recommended templates, and sending identity information of the recommended templates to mobile phone terminals of students, wherein the identity information of the recommended templates comprises graduation colleges, professions, college subjects, graduation years and development coefficients of the recommended templates.
Further, the value determination process of u includes:
if the reference object engages in a related industry where the occupation is a university major, u =1;
if the reference object is engaged in a professional that is not a college professional related professional, u =0.
Further, the working method of the cloud computing-based auxiliary system for the student department comprises the following steps:
the method comprises the following steps: the institution analysis module is used for carrying out intention institution analysis on students intending to universities and colleges, obtaining institution coefficients by analyzing the admission data, graduation data and 32900university data, and selecting whether to replace the intention institutions and screening out alternative institutions according to the students of the selected intention institutions and colleges by the students;
step two: the professional analysis module performs professional analysis on students of the selected intention colleges, and the students select the professions according to employment coefficients and examination coefficients;
step three: the template analysis module is used for carrying out template analysis on students without intention colleges and universities, screening out reference objects through the ranking of the high school exams, selecting a recommended template for the students according to the reference objects and the keywords selected by the students by the template recommendation model, and providing reference for the division selection of the students according to the colleges and universities, the professions and the college subject requirements corresponding to the professions of the recommended template.
The invention has the following beneficial effects:
1. the institution analysis module is used for performing institution analysis on students with the intention institutions, the admission condition and the graduation condition of the future year of the intention institutions are analyzed, the examination reporting difficulty, the learning difficulty and the graduation difficulty of the intention institutions are comprehensively analyzed to obtain institution coefficients, and the students can know the overall learning difficulty of the institutions through the institution coefficients and then consider whether to replace the intention institutions or not;
2. the students can select whether to change the intention specialties or not according to the employment coefficient and the investigation coefficient, and meanwhile, when the students select not to change the intention specialties but change the intention colleges, the students can consider alternative colleges preferentially, the students can fully know the overall conditions of competition, reading and employment of the intention colleges and the intention specialties before selecting the subject, and the students can make optimized selection conveniently after self-balancing;
3. the template analysis module can be used for carrying out template matching on students without intention colleges and intention specialties, the reference objects are screened out in the grade city where the students are located through senior high school exam ranking, then the development coefficient is calculated through development data after graduations of the reference object universities, the students can select interested industries for template matching by themselves, the screened recommendation templates are the best reference objects in the respective fields, so that references can be provided for the students through the scores of the reference objects selectively, subject-to-subject recommendation is carried out on the students without clear targets, in addition, the best reference objects in the respective fields can be used as the recommendation templates to establish forward guidance for the students, the scores of the cities, the living backgrounds and the senior high school exams of the recommendation objects are close to the students, the influence and the persuasion of the forward guidance are improved, and the encouragement effect can be played on the students with different learning scores.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of the system of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the cloud-computing-based student branch-of-subject auxiliary system comprises a cloud analysis platform, wherein the cloud analysis platform is in communication connection with an institution analysis module, a professional analysis module and a template analysis module.
The institution analysis module is used for carrying out intention institution analysis on students intending to go to institutions: the institution data is that aiming at students with the intention colleges, the students can know the students and make decisions by themselves according to the colleges selected by the students, and the students select the students and then carry out subject recommendation according to the intentions selected by the students;
the admission data is the ratio of the number of persons admitted to the regional city of the students by the intention colleges to the total number of persons admitted to the intention objects;
the graduation data is the ratio of the number of graduates in the intention colleges to the total number of the students in the corresponding student's year of school;
32900the trade data is the ratio of the number of people who finish closing or refunding in the reading period of the due institution to the total number of people who enter the due school in the year of entering the school;
summing the recorded data of the last three years and taking the average number to obtain a recorded analysis value LQ; summing graduation data of the last three years and taking an average number to obtain a graduation analysis value BY; the method comprises the following steps of summing up the \32900capitaldata of the last three years and obtaining an average number to obtain an \32900capitalanalysis value YY;
obtaining a college coefficient YX BY a formula YX = (alpha 1 multiplied BY LQ + alpha 2 multiplied BY)/(alpha 3 multiplied BY YY), wherein alpha 1, alpha 2 and alpha 3 are proportionality coefficients, and alpha 3 is more than alpha 2 and more than alpha 1 and more than 0; the higher the value of the institution coefficient YX is, the smaller the difficulty of the student in the study, the reading of the intent institution and the smooth graduation of the intent institution is;
the institution analysis module sends the institution coefficients to a mobile phone terminal of the student, the student selects whether to change the intention institution or not after receiving the institution coefficients, if the student changes the intention institution, analysis is performed again according to the intention institution re-input by the student, and the student generally has subjective knowledge about the selected intention institution, so that the institution coefficients obtained through calculation of historical data can objectively reflect the whole reading difficulty of the intention institution, and the student can make a selection again after objective knowledge; if the students do not change the intention colleges, alternative colleges are screened for the students, and if the students do not select the intention change specialty and change the intention colleges during subsequent professional analysis, the same specialty can be screened from the alternative colleges preferentially for the students to select;
the screening process of the alternative institutions comprises the following steps: acquiring institution thresholds YXmin and YXmax of institutions through formulas YXmin = a1 XYX and YXmax = a2 XYX, wherein YXmin is a minimum institution threshold, YXmax is a maximum institution threshold, the institution thresholds YXmin and YXmax form a screening range, acquiring institution coefficients of all universities in grade city of the institution to which the institution is located, and marking the universities with the institution coefficients within the screening range as alternative universities.
The professional analysis module is used for performing professional analysis on students who complete the analysis of colleges and universities: the students input intention specialities into the professional analysis module through the mobile phone terminal, the professional analysis module marks the intention specialities as mark objects after receiving the intention specialities, and employment data and examination data of graduates of the mark objects in the last three years are obtained;
the employment data of graduates with the graduation age within one year is the difference SC between the time of employment of the graduates and the time of leaving and leaving, and the unit is month;
the employment data of graduates with the graduation age of one to two years is a ratio ZH of the number of graduate transfer lines to the total number of graduates in the same marked object;
employment data of graduates with the graduation years of two to three years is annual income SR of the graduates, and the unit is ten thousand yuan;
by the formula
Obtaining a employment coefficient JY, wherein the employment coefficient is a numerical value of the employment difficulty and the employment prospect after the graduation of graduates of an intention specialty, the larger the numerical value of the employment coefficient is, the smaller the employment difficulty after the graduation of the graduates of the intention specialty is, the better the employment prospect is, and the professional selection can be performed on students planning the employment after the graduation by referring to the employment coefficient, wherein beta 1, beta 2 and beta 3 are proportional coefficients, beta 3 is more than beta 2 and more than beta 1, k is a correction factor, and the value of k is 2.34;
the examination data acquisition process of the marked object comprises the following steps: marking the total number of the research students in the last three years of the marked object as BY, marking the total number of the research students reporting examinations in the last three years of the marked object as BK, and marking the total number of the research students taking examinations in the last three years of the marked object as TG; obtaining an investigation coefficient KY of the marked object through a formula KY = (gamma 1 × BY + gamma 2 × TG)/(gamma 3 × BK), wherein the investigation coefficient is a numerical value reflecting the success rate of graduation study of an intention specialty, the higher the numerical value of the investigation coefficient is, the higher the success rate of graduation study of the intention specialty is, and the specialty can be selected BY referring to the investigation coefficient aiming at students planning investigation, wherein gamma 1, gamma 2 and gamma 3 are proportionality coefficients, and gamma 1 is more than gamma 2 and more than gamma 3 is more than 1;
the professional analysis module sends the employment coefficient JY and the investigation coefficient KY of the marked object to a mobile phone terminal of the student, and the student selects whether to replace the intention specialty after receiving the employment coefficient JY and the investigation coefficient KY:
if the student selects to change the intention specialty, confirming again through the institution analysis module whether the student selects to change the intention institution:
if the student selects to replace the intention colleges, the college analysis module sends the alternative colleges to the mobile phone terminal of the student, and the student selects the intention colleges from the alternative colleges or re-inputs the intention colleges;
if the students choose not to change the intention colleges, professional screening is carried out in the intention colleges until the students choose not to change the intention specialties after professional analysis;
if the students choose not to change the intention speciality, acquiring the examination reporting data of the marked object, sending the examination reporting data of the marked object to mobile phone terminals of the students by the speciality analysis module, and after receiving the examination reporting data of the marked object, the students choose subjects according to examination reporting requirements of the marked object, wherein the examination reporting data of the marked object is subject requirements of the corresponding speciality on the examination reporting students.
The template analysis module is used for carrying out template analysis on students without intention colleges: the method comprises the steps that students without intention colleges are marked as recommended objects, grade city ranks of the recommended objects in high school exams are obtained and marked as standard ranks, the ranks of the L1 before and after the standard ranks are respectively marked as a minimum standard and a maximum standard, students with different learning scores can play a role in encouragement, the L1 is a preset quantity constant, the minimum standard and the maximum standard form a standard range, all students with the ranks within the standard range in the high school exams of the grade city where the recommended objects in the years from M1 to M2 are marked as reference objects, the M1 and the M2 are preset years, the M2 is more than the M1, the number of the years of the M1 and the M2 can be selected by the students according to personal preference and the higher exam division system of the next year, the city where the recommended objects are located, the living background and the high school exams are all matched with the students, and the impact and persuasion forward guidance is improved;
screening a template of a recommended object from the reference objects by adopting a template recommendation model and recommending: acquiring the graduation year of a reference object and marking the graduation year as BN, acquiring the current annual income of the reference object and marking the annual income as NS, acquiring the number of managers at the position of the reference object and marking the number of the managers as GL, and acquiring the development coefficient of the managers by a formula FZ = u x (theta 1 x NS/BN + theta 2 x GL), wherein theta 1, theta 2 and u are proportionality coefficients, and theta 1 is more than theta 2 and more than 1; the value determination process of u comprises the following steps: if the reference object engages in a related industry where the occupation is a university major, u =1; if the occupation of the reference object is not the related professional of the university professional, u =0, and if the occupation of the reference object is not related to the university professional, the corresponding reference object is not considered as a recommendation template;
the method comprises the steps of classifying reference objects according to industries where the reference objects are located and generating keywords, selecting the industries by the recommended objects through the selected keywords, marking the selected industries as selected industries, marking three reference objects with the highest development coefficients in the selected industries as recommended templates, and sending identity information of the recommended templates to mobile phone terminals of students, wherein the identity information of the recommended templates comprises graduation colleges, professions, college subjects, graduation years and development coefficients of the recommended templates.
A cloud computing-based auxiliary analysis method for student departments comprises the following steps:
the method comprises the following steps: the institution analysis module analyzes the admission data, the graduation data and the 32900professional data to obtain institution coefficients, the students select whether to replace the intended institution according to the institution coefficients, and screen out alternative institutions for the students of the selected intention institution;
step two: the professional analysis module performs professional analysis on students of the selected intention colleges, and the students select the professions according to employment coefficients and examination coefficients;
step three: the template analysis module is used for carrying out template analysis on students without intention colleges and universities, screening out reference objects through the ranking of the high school exams, selecting a recommended template for the students according to the reference objects and the keywords selected by the students by the template recommendation model, and providing reference for the division selection of the students according to the colleges and universities, the professions and the college subject requirements corresponding to the professions of the recommended template.
A student branch auxiliary system based on cloud computing is characterized in that when the system works, an institution analysis module is adopted to conduct intention institution analysis on students intending to an institution to obtain institution coefficients, the students select whether to replace the intention institution or not according to the institution coefficients, and select alternative institutions for the students of the selected intention institution; the professional analysis module performs professional analysis on students in the selected intention colleges, and the students select the professionals according to employment coefficients and examination coefficients; the template analysis module is used for carrying out template analysis on students without intention colleges and universities, the reference objects are screened out through the ranking of the high school entrance examination, and the template recommendation model is used for selecting the recommendation template for the students according to the reference objects and the keywords selected by the students.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
The formulas are obtained by acquiring a large amount of data and performing software simulation, and the coefficients in the formulas are set by the technicians in the field according to actual conditions; such as: formula KY = (γ 1 × BY + γ 2 × TG)/(γ 3 × BK); collecting multiple groups of sample data by the technicians in the field and setting a corresponding examination coefficient for each group of sample data; substituting the set investigation coefficient and the acquired sample data into formulas, forming a ternary linear equation set by any three formulas, screening the calculated coefficients and taking the mean value to obtain values of gamma 1, gamma 2 and gamma 3 which are respectively 3.57, 2.88 and 2.45;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding investigation coefficient is preliminarily set for each group of sample data by a person skilled in the art; if the proportional relation between the parameters and the quantified values is not affected, the examination coefficient is inversely proportional to the number of the people under investigation.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (9)
1. The auxiliary system for the student division based on the cloud computing is characterized by comprising a cloud analysis platform, wherein the cloud analysis platform is in communication connection with an institution analysis module, a professional analysis module and a template analysis module;
the institution analysis module is used for carrying out intention institution analysis on students intending to pass institutions and obtaining institution coefficients, the institution analysis module sends the institution coefficients to mobile phone terminals of the students, and the students select whether to change the intention institutions or not after receiving the institution coefficients;
if the student changes the intention colleges and universities, the intention colleges and universities are analyzed again;
if the student does not change the intention colleges, screening alternative colleges for the student;
the professional analysis module is used for performing professional analysis on students who complete the analysis of colleges and universities and obtaining employment coefficients and examination coefficients of intention specialties, the professional analysis module sends the employment coefficients and the examination coefficients of the marked objects to mobile phone terminals of the students, and the students select whether to change the intention specialties or not after receiving the employment coefficients and the examination coefficients;
the template analysis module is used for carrying out template analysis on students without intention colleges: the method comprises the steps of marking students without intention colleges as recommended objects, obtaining grade city ranking of the recommended objects in high-school exams and marking the grade city ranking as standard ranking, marking the ranking of L1 before and after the standard ranking as the lowest standard and the highest standard respectively, wherein L1 is a preset quantity constant, forming a standard range by the lowest standard and the highest standard, marking all students with ranking in the standard range in the high-school exams of the grade city where the recommended objects in the years of M1-M2 are as reference objects, wherein M1 and M2 are preset years, and M2 is larger than M1.
2. The cloud-computing-based student branch aid system as claimed in claim 1, wherein the acquisition process of the institution coefficients comprises: marking students of the intentional academy as selected students, inputting the students into an intention academy through a mobile phone terminal, marking the intention academy as an intention object after the intention academy is received by the institution analysis module, and acquiring the recorded data, graduation data and 32900professional data of the intention object in the last three years;
summing the recorded data of the last three years and taking the average number to obtain a recorded analysis value LQ; summing graduation data of the last three years and taking the average number to obtain a graduation analysis value BY; carrying out summation on the \ 32900and industry data of the last three years and obtaining an average number to obtain an \ -32900and an industry analysis value YY;
the college coefficient YX is obtained BY the formula YX = (α 1 × LQ + α 2 × BY)/(α 3 × YY), where α 1, α 2, and α 3 are proportionality coefficients, and α 3 > α 2 > α 1 > 0.
3. The cloud-computing-based auxiliary system for the departments of the students, as claimed in claim 2, wherein the admission data is a ratio of the number of persons admitted by the intention institution in the class city where the students are located to the total number of persons admitted by the intention object; the graduation data is the ratio of the number of graduates in the intention colleges to the total number of the students in the corresponding student's year of school; 32900900the trade data is the ratio of the number of people who finish the ending or refunding of the due student of the intention institution during the reading period to the total number of people who enter the due student in the year of entering the school.
4. The cloud-computing-based student branch aid system as claimed in claim 3 wherein the screening process of the alternative institutions comprises: acquiring institution thresholds YXmin and YXmax of institutions through formulas YXmin = a1 XYX and YXmax = a2 XYX, wherein YXmin is a minimum institution threshold, YXmax is a maximum institution threshold, the institution thresholds YXmin and YXmax form a screening range, acquiring institution coefficients of all universities in grade city of the institution to which the institution is located, and marking the universities with the institution coefficients within the screening range as alternative universities.
5. The cloud-computing-based student branch aid system as claimed in claim 4, wherein the employment coefficient obtaining process comprises: the students input intention specialities into the professional analysis module through the mobile phone terminal, the professional analysis module marks the intention specialities as mark objects after receiving the intention specialities, and employment data of graduates of the mark objects in the last three years are obtained;
the employment data of graduates with the graduation age within one year is the difference SC between the time of employment of the graduates and the time of leaving and leaving, and the unit is month;
the employment data of graduates with the graduation age of one to two years is a ratio ZH of the number of graduate transfer lines to the total number of graduates in the same marked object;
employment data of graduates with the graduation years of two to three years is annual income SR of the graduates, and the unit is ten thousand yuan;
by the formula
Obtaining an employment coefficient JY, wherein beta 1, beta 2 and beta 3 are proportional coefficients, beta 3 is more than beta 2 and more than beta 1 is more than 1, k is a correction factor, and the value of k is 2.34.
6. The cloud computing-based student affiliation assistance system according to claim 5, wherein the process of obtaining the research coefficients includes: marking the total number of the research students in the last three years of the marked object as BY, marking the total number of the research students reporting examinations in the last three years of the marked object as BK, and marking the total number of the research students taking examinations in the last three years of the marked object as TG; an investigation coefficient KY of the marked object is obtained through a formula KY = (gamma 1 × BY + gamma 2 × TG)/(gamma 3 × BK), wherein gamma 1, gamma 2 and gamma 3 are proportionality coefficients, and gamma 1 > gamma 2 > gamma 3 > 1.
7. The cloud computing-based student branch aid system as claimed in claim 6 wherein the process of receiving professional selection of employment and research coefficients by students comprises:
if the student selects to change the intention specialty, confirming again through the institution analysis module whether the student selects to change the intention institution:
if the student selects to replace the intended colleges, the college analysis module sends the alternative colleges to the mobile phone terminals of the student, and the student selects the intended colleges from the alternative colleges or re-inputs the intended colleges;
if the students choose not to change the intention colleges, professional screening is carried out in the intention colleges until the students choose not to change the intention specialties after professional analysis;
if the students choose not to change the intention speciality, acquiring the examination reporting data of the marked object, sending the examination reporting data of the marked object to mobile phone terminals of the students by the speciality analysis module, and after receiving the examination reporting data of the marked object, the students choose subjects according to examination reporting requirements of the marked object, wherein the examination reporting data of the marked object is subject requirements of the corresponding speciality on the examination reporting students.
8. The cloud-computing-based student branch aid system as claimed in claim 7 wherein the template recommendation model screens out and recommends templates for recommended objects from reference objects: the method comprises the steps of obtaining the graduation age of a reference object and marking the graduation age as BN, obtaining the current annual income of the reference object and marking the current annual income as NS, obtaining the number of managers of the position where the reference object is located and marking the number of the managers as GL, and obtaining the development coefficient of the managers through a formula FZ = u x (theta 1 x NS/BN + theta 2 x GL), wherein theta 1, theta 2 and u are proportional coefficients, and theta 1 is more than theta 2 and more than 1;
the method comprises the steps of classifying reference objects according to industries where the reference objects are located and generating keywords, selecting the industries by the recommended objects through the selected keywords, marking the selected industries as selected industries, marking three reference objects with the highest development coefficients in the selected industries as recommended templates, and sending identity information of the recommended templates to mobile phone terminals of students, wherein the identity information of the recommended templates comprises graduation colleges, professions, college subjects, graduation years and development coefficients of the recommended templates.
9. The cloud computing-based student triage assistance system according to claim 1, wherein the working method of the cloud computing-based student triage assistance system comprises the following steps:
the method comprises the following steps: the institution analysis module is used for carrying out intention institution analysis on students intending to universities and colleges, obtaining institution coefficients by analyzing the admission data, graduation data and 32900university data, and selecting whether to replace the intention institutions and screening out alternative institutions according to the students of the selected intention institutions and colleges by the students;
step two: the professional analysis module performs professional analysis on students of the selected intention colleges, and the students select the professions according to employment coefficients and examination coefficients;
step three: the template analysis module is used for carrying out template analysis on students without intention colleges and universities, screening out reference objects through the ranking of the high school exams, selecting a recommended template for the students according to the reference objects and the keywords selected by the students by the template recommendation model, and providing reference for the division selection of the students according to the colleges and universities, the professions and the college subject requirements corresponding to the professions of the recommended template.
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