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

G. Rácz, A. Sali, K. Schewe. Semantic matching strategies for job recruitment: A comparison of new and known approaches. volume 9616, pages 149-168, DOI 10.1007/978-3-319-30024-5_9, 3, 2016.

Autoren
  • Gabór Rácz
  • Atila Sali
  • Klaus-Dieter Schewe
Editoren
  • Marc Gyssens
  • Guillermo Simari
BuchFoundations of Information and Knowledge Systems - Proc. FoIKS 2016
TypIn Konferenzband
VerlagSpringer
SerieLecture Notes in Computer Science
Band9616
DOI10.1007/978-3-319-30024-5_9
ISBN978-3-319-30023-8
Monat3
Jahr2016
Seiten149-168
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.