Semantic matching strategies for job recruitment: A comparison of new and known approaches

Authors Gabór Rácz
Atila Sali
Klaus-Dieter Schewe
Editors Marc Gyssens
Guillermo Simari
Title Semantic matching strategies for job recruitment: A comparison of new and known approaches
Booktitle Foundations of Information and Knowledge Systems - Proc. FoIKS 2016
Type in proceedings
Publisher Springer
Series Lecture Notes in Computer Science
Volume 9616
ISBN 978-3-319-30023-8
DOI 10.1007/978-3-319-30024-5_9
Month March
Year 2016
Pages 149-168
SCCH ID# 1625
Abstract

A profile describes a set of skills a person may have or a set of skills required for a particular job. Profile matching aims to determine how well a given profile fits to a requested profile. The research reported in this paper starts from exact matching measure of [21]. It is extended then by matching filters in ontology hierarchies, since profiles naturally determine filters in the subsumption relation. Next we take into consideration similarities between different skills that are not related by the subsumption relation. Finally, a totally different approach, probabilistic matching based on the maximum entropy model is analyzed.