The study on intelligent decision and personalized recommendation of job information service

Abstract

With the rapid development of the Internet, the vast majority of college students have been applying for jobs online mainly. For the applicants, while the upside of the Internet is to provide considerable and various job information, it may take them a great deal of time and energy to pick the fitting post from as well. Currently, job-hunting Web sites demonstrate all sorts of information through integration and classification, requiring users to manually retrieve to find the best for them. Combining the key technology of personalized recommendation service and online job-seeking of graduates, the paper designs and implements the employment information recommendation service for college students. The concrete procedures include adopting recommendation algorithm and similarity calculating method that cater to job information based on data mining, intelligent decisions, analysis of users’ preference and information integration and recommendation and testing in terms of certain situations or data features. It achieves the desired recommendation result.