Research And Development Of Employment Recommendation System In Higher Vocational Colleges Based On Collaborative Filtering

For a long time,college students' employment has been a hot topic in colleges and universities.With the development of the Internet,a large number of job-hunting websites have been operating.Most of these sites are socially oriented,and there is a risk to job seekers' personal information.At the same time,due to the huge data,corporate recruiters and university staff need to spend a lot of energy to verify the accuracy of the information.In order to improve the employment rate of students in higher vocational colleges,this paper develops an employment recommendation system based on collaborative filtering.Compared with the traditional employment recommendation system,the system has two main advantages:first,it meets the employment interest of students in higher vocational colleges.Ii.Also meet the recruitment standards of recruitment enterprises.The main work of this paper is:first,change system based on the improved collaborative filtering algorithm,added some employment factors influencing students'employment,such as:education,professional courses,political affiliation,grades,gender,English,computer skill,students,students and so on the objective presentation of characteristic value of employment.This paper USES information gain rate in information theory to determine the influence degree of feature attribute.The information gain rate can be used to determine the importance of students' characteristic attributes in the employment selection of fresh graduates,and then determine the weight coefficient of each characteristic attribute.Second,the relatively accurate in order to find the initial clustering center in traditional clustering algorithm,this paper based on the improved K Means clustering algorithm,using the principle of minimum spanning tree to solve the shortest path problem,and be sure to find the clustering center is able to make on behalf of this type of data:recently,the distance of the feature attribute,even if the same students wiithout similar attributes farthest students.Finally,according to the students'interest rate of enterprise units,select the highest degree of previous generation of students,and recommend the employment units of previous graduates to fresh graduates.Therefore,it is more targeted for students and employers to establish and develop the management system for students' employment recommendation.It is also conducive to the improvement of the general employment status of the society.