A Smart Approach for Matching, Learning and Querying Information from the Human Resources Domain

Jorge Martinez-Gil, Alejandra Lorena Paoletti, Klaus-Dieter Schewe

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

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. In fact, 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 automatically 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.
Original languageEnglish
Title of host publicationNew Trends in Databases and Information Systems: ADBIS 2016 Short Papers and Workshops, BigDap, DCSA, DC, Prague, Czech Republic, August 28-31, 2016, Proceedings
Editors Ivanovic Mirjana, Thalheim Bernhard, Catania Barbara, Schewe Klaus-Dieter, Kirikova Marite, Saloun Petr, Dahanayake Ajantha, Cerquitelli Tania, Baralis Elena, Michiardi Pietro
Place of PublicationCham
PublisherSpringer
Pages157-167
Number of pages11
Volume637
ISBN (Print)978-3-319-44066-8
DOIs
Publication statusPublished - Aug 2016

Fields of science

  • 102010 Database systems
  • 102014 Information design
  • 102015 Information systems
  • 102028 Knowledge engineering
  • 102030 Semantic technologies
  • 102033 Data mining
  • 509018 Knowledge management

JKU Focus areas

  • Computation in Informatics and Mathematics

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