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

Autoren Jorge Martinez Gil
Lorena Paoletti
Klaus-Dieter Schewe
Editoren
TitelA smart approach for matching, learning and querying information from the human resources domain
BuchtitelNew Trends in Databases and Information Systems - Proc. ADBIS 2016 Short Papers and Workshops
Typin Konferenzband
VerlagSpringer
SerieCommunications in Computer and Information Science
Band637
ISBN978-3-319-44065-1
DOI10.1007/978-3-319-44066-8_17
MonatAugust
Jahr2016
Seiten157-167
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.