Improving the Accuracy of Job Search with Semantic Techniques

  • Malgorzata Mochol
  • Holger Wache
  • Lyndon Nixon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4439)

Abstract

In this paper we introduce a prototype job portal which uses semantically annotated job offers and applicants. In our opinion, using Semantic Web technologies substantially increase market transparency, lower transaction costs and speed up the procurement process. However adding semantics is not a panacea for everything. We identify some outstanding problems in job search using the system and outline how the technique of query approximation can be the basis for a solution. Through an Industry-Research co-operation we are extending the prototype with these semantic techniques to demonstrate a more accurate job search.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Nixon, L., et al.: Towards a successful transfer of knowledge-based technology to European Industry. In: Proc. of the 1st Workshop on Formal Ontologies Meet Industry (FOMI 2005) (2005)Google Scholar
  2. 2.
    Bizer, C., et al.: The Impact of Semantic Web Technologies on Job Recruitment Processes. In: International Conference Wirtschaftsinformatik (WI’05) (2005)Google Scholar
  3. 3.
    Bizer, C., Mochol, M., Westphal, D.: Recruitment, report (April 2004)Google Scholar
  4. 4.
    Bizer, C., Seaborne, A.: D2RQ - Treating Non-RDF Databases as Virtual RDF Graphs. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, Springer, Heidelberg (2004)Google Scholar
  5. 5.
    Bourse, M., et al.: Human Resource Management and Semantic Web Technologies. In: Proc. of the 1st International Conference on Information Communication Technologies: from Theory to Applications (2004)Google Scholar
  6. 6.
    Dolog, P., Stuckenschmidt, H., Wache, H.: Robust query processing for personalized information access on the semantic web. In: Larsen, H.L., et al. (eds.) FQAS 2006. LNCS (LNAI), vol. 4027, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Keim, T., et al.: Recruiting Trends 2005. Working Paper No. 2005-22. efinance Institut. Johann-Wolfgang-Goethe-Universität Frankfurt am Main (2005)Google Scholar
  8. 8.
    Kießling, W., Köstler, G.: Preference sql - design, implementation, experiences. In: Proc. of 28th International Conference on Very Large Data Bases, pp. 990–1001. Morgan Kaufmann, San Francisco (2002)CrossRefGoogle Scholar
  9. 9.
    Lacroix, M., Lavency, P.: Preferences; putting more knowledge into queries. In: Stocker, P.M., Kent, W., Hammersley, P. (eds.) VLDB’87, Proceedings of 13th International Conference on Very Large Data Bases, Brighton, England, September 1-4, 1987, pp. 217–225. Morgan Kaufmann, San Francisco (1987)Google Scholar
  10. 10.
    Lau, T., Sure, Y.: Introducing ontology-based skills management at a large insurance company. In: Proc. of the of the Modellierung 2002, pp. 123–134 (2002)Google Scholar
  11. 11.
    Mülder, W.: Personalinformationssysteme - Entwicklungsstand, Funktionalität und Trends. Wirtschaftsinformatik (Special Issue IT Personal) 42, 98–106 (2000)Google Scholar
  12. 12.
    Mochol, M., Paslaru Bontas, E.: Practical Guidelines for Building Semantic eRecruitment Applications. In: International Conference on Knowledge Management, Special Track: Advanced Semantic Technologies (AST’ 06) (2006)Google Scholar
  13. 13.
    Monster. Monster Deutschland and TMP Worldwide: Recruiting Trends 2004. In: 2. Fachsymposium für Personalverantwortliche. Institut für Wirtschaftsinformatik der Johann Wolfgang Goethe-Universität Frankfurt am Main (2003)Google Scholar
  14. 14.
    Oldakowski, R., Bizer, C.: SemMF: A Framework for Calculating Semantic Similarity of Objects Represented as RDF Graphs. In: Gil, Y., et al. (eds.) ISWC 2005. LNCS, vol. 3729, Springer, Heidelberg (2005)Google Scholar
  15. 15.
    Paslaru Bontas, E., Mochol, M.: Towards a reuse-oriented methodology for ontology engineering. In: Proc. of 7th International Conference on Terminology and Knowledge Engineering (TKE 2005) (2005)Google Scholar
  16. 16.
    Paslaru Bontas, E., Mochol, M., Tolksdorf, R.: Case Studies on Ontology Reuse. In: Proc. of the 5th International Conference on Knowledge Management (iKnow05) (2005)Google Scholar
  17. 17.
    Poole, J., Campbell, J.A.: A Novel Algorithm for Matching Conceptual and Related Graphs. In: Ellis, G., et al. (eds.) ICCS 1995. LNCS, vol. 954, pp. 293–307. Springer, Heidelberg (1995)Google Scholar
  18. 18.
    Sowa, F., Bremen, A., Apke, S.: Entwicklung der Kompetenz-Ontologie für die Deutsche Montan Technologie GmbH (2003)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Malgorzata Mochol
    • 1
  • Holger Wache
    • 2
  • Lyndon Nixon
    • 1
  1. 1.Freie Universität Berlin, Institut für Informatik, Takustr. 9, D-14195 BerlinGermany
  2. 2.Vrije Universiteit Amsterdam, Artificial Intelligence Department de Boelelaan 1081a, NL-1081HV, AmsterdamThe Netherlands

Personalised recommendations