A smart approach for matching, learning and querying information from the human resources domain

Authors Jorge Martinez Gil
Lorena Paoletti
Klaus-Dieter Schewe
Editors
Title A smart approach for matching, learning and querying information from the human resources domain
Booktitle New Trends in Databases and Information Systems - Proc. ADBIS 2016 Short Papers and Workshops
Type in proceedings
Publisher Springer
Series Communications in Computer and Information Science
Volume 637
ISBN 978-3-319-44065-1
DOI 10.1007/978-3-319-44066-8_17
Month August
Year 2016
Pages 157-167
SCCH ID# 1656
Abstract

We face the complex problem of timely, accurate and mutually satisfactory mediation between job offers and suitable applicant profiles by means of semantic processing techniques. This problem has become a major challenge for all public and private recruitment agencies around the world as well as for employers and job seekers. It is widely agreed that smart algorithms for matching, learning, and querying job offers and candidate profiles will provide a key technology of high importance and impact and will help to counter the lack of skilled labor and/or appropriate job positions for unemployed people. Additionally, such a framework can support global matching aiming at finding an optimal allocation of job seekers to available jobs, which is relevant for independent employment agencies, e.g. in order to reduce unemployment.