Pre-selection of Recruitment Candidates Using Case Based Reasoning

The cost of manually preselecting potential candidates have risen and employers are searching for methods to automate the pre-selection of candidates to fill in the vacancies at their organizations. Job portal services have proved to be the most successful and popular information services on the internet. Being more selective through selection especially from large pool of applicants will be able to decrease the possibility of hiring the poor performing individuals. The proposed system enables the employer to select the right candidate quicker and by using internet for recruitment has the advantage of faster cycle time, cheaper, and more convenient for both the employers and the job seekers. However, most job portal search engines rely on exact-match retrieval constraints. For this type of matching, a rule based approach was normally utilized. To this end, a prototype called JOBMatching^© using CBR engine for matching purposes has been developed, validated and evaluated. JOBMatching^© system comprises of databases of graduates as well as a match engine that incorporates Case Based Reasoning to increase its competitive advantage. CBR recommends the best candidate suitable with the job requirement using similarity measurement. Based on the feedback, JOBMatching^© system facilitates the pre-selection of candidates for employment.