Recruit Recommendation Based On The Wisdom Of Expert

The rapid progress of Internet has been making information exchange more convenient andpromoting new opportunities in many industries. In recruitment businesses, Internet-basedtechnologies make it easy for jobseekers to find desirable jobs, and at the same time, forrecruiters to identify suitable candidates among all the applicants.A large amount of new information about new vacancies is created and posted by onlinerecruitment businesses on a daily basis, which makes it difficult for a jobseeker to find suitablevacancies when making his/her query. This is not helped by the even larger amount of historicaldata which could be conflicting and misleading. It is desirable to provide a jobseekerpersonalized service which is based on his/her backgrounds such as experience, preference, aswell as many other factors. Collective filtering is one of the most widely-used recommendationapproaches to provide personalized service. However, it still has difficulties in dealing withsparse and noisy data when the data set is huge, which is common in practice.This paper presents an effective approach to personalized recruitment service based on acombination of collaborative filtering and the wisdom of experts. It first defines expert-jobseeker,then provides an algorithm which uses the jobseekers’ ratings on vacancies to identifyexpert-jobseekers among them, before a collective-filtering-based algorithm be proposed toprovide a jobseeker with suitable vacancies.Preliminary experiments have been carried out on the data provided by job168.com, whichdemonstrated the effectiveness and efficiency of the proposed approach.