Modern Job Search Using Ontology Approach in Online Job Portals

Abstract

 Internet has come to be the principal medium for Human Resource Management, especially job recruitment and employment process. Classical job recruitment portals on the Internet depend on the keyword-based search approach in undeniable textual content to detect jobs. However, this method consequences in excessive recall, low precision and barring thinking about the semantic similarity between these keywords. Many researchers have proposed semantic matching procedures with the aid of growing ontologies as a reference to decide matching accuracy qualitatively, alternatively these techniques do no longer quantify how carefully matched candidates and employers are, primarily based on core skills. This paper proposes a method that makes use of an ontology-based strategy to decorate key-word looking out via leveraging on the similarity between ideas in the ontology, which symbolize core abilities wished and required for a job in order to decide how carefully matched an applicant is to a job commercial and vice-versa. This was once performed with the aid of creating a CV Ontology based totally on core skills, annotating applicant profiles and job profiles the use of a frequent vocabulary and editing the semantic notion similarity algorithm to precisely compute and rank matching rating between profiles when a question is performed. The outcomes confirmed upgrades of 54% and 36% for Recall and F-measure respectively, over [21].