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Extending Knowledge-Based Profile Matching in the Human Resources Domain

Part of the Lecture Notes in Computer Science book series (LNISA,volume 9262)


In the Human Resources domain the accurate matching between job positions and job applicants profiles is crucial for job seekers and recruiters. The use of recruitment taxonomies has proven to be of significant advantage in the area by enabling semantic matching and reasoning. Hence, the development of Knowledge Bases (KB) where curricula vitae and job offers can be uploaded and queried in order to obtain the best matches by both, applicants and recruiters is highly important. We introduce an approach to improve matching of profiles, starting by expressing jobs and applicants profiles by filters representing skills and competencies. Filters are used to calculate the similarity between concepts in the subsumption hierarchy of a KB. This is enhanced by adding weights and aggregates on filters. Moreover, we present an approach to evaluate over-qualification and introduce blow-up operators that transform certain role relations such that matching of filters can be applied.


  • HR Domain
  • Human Resources
  • Application Profile
  • Matching Measurement
  • Lattice-like Structure

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The research reported in this paper was supported by the Austrian Forschungsförderungsgesellschaft (FFG) for the Bridge project “Accurate and Efficient Profile Matching in Knowledge Bases” (ACEPROM) under contract 841284.

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  1. European dictionary of skills and competences.

  2. International standard classification of education.

  3. International standard classification of occupations.

  4. Baader, F., Bürckert, H.-J., Heinsohn, J., Hollunder, B., Müller, J., Nebel, B., Nutt, W., Profitlich, H.-J.: Terminological knowledge representation: a proposal for a terminological logic. In: Description Logics, pp. 120–128 (1991)

    Google Scholar 

  5. Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, Cambridge (2003)

    Google Scholar 

  6. Cimiano, P., Hotho, A., Stumme, G., Tane, J.: Conceptual knowledge processing with formal concept analysis and ontologies. In: Eklund, P. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 189–207. Springer, Heidelberg (2004)

    CrossRef  Google Scholar 

  7. Grau, B.C., Horrocks, I., Motik, B., Parsia, B., Patel-Schneider, P.F., Sattler, U.: OWL 2: The next step for OWL. J. Web Sem. 6(4), 309–322 (2008)

    CrossRef  Google Scholar 

  8. Gruber, T.R.: Toward principles for the design of ontologies used for knowledge sharing? Int. J. Hum. Comput. Stud. 43(5–6), 907–928 (1995)

    CrossRef  Google Scholar 

  9. Klein, M.C.A., Broekstra, J., Fensel, D., van Harmelen, F., Horrocks, I.: Ontologies and schema languages on the web. In: Spinning the Semantic Web: Bringing the World Wide Web to its Full Potential [outcome of a Dagstuhl seminar], pp. 95–139 (2003)

    Google Scholar 

  10. Looser, D., Ma, H., Schewe, K.-D.: Using formal concept analysis for ontology maintenance in human resource recruitment. In: Ninth Asia-Pacific Conference on Conceptual Modelling, APCCM 2013, Adelaide, Australia, January 29–Feburary 1 2013, pp. 61–68 (2013)

    Google Scholar 

  11. Mochol, M., Nixon, L.J.B., Wache, H.: Improving the recruitment process through ontology-based querying. In: Proceedings of the First International Workshop on Applications and Business Aspects of the Semantic Web (SEBIZ 2006) Collocated with the 5th International Semantic Web Conference (ISWC-2006), Athens, Georgia, USA, 6 November 2006 (2006)

    Google Scholar 

  12. Mochol, M., Wache, H., Nixon, L.J.B.: Improving the accuracy of job search with semantic techniques. In: Abramowicz, W. (ed.) BIS 2007. LNCS, vol. 4439, pp. 301–313. Springer, Heidelberg (2007)

    CrossRef  Google Scholar 

  13. Popov, N., Jebelean, T.: Semantic matching for job search engines: a logical approach. Technical report 13–02, RISC Report Series. University of Linz, Austria (2013)

    Google Scholar 

  14. Zavitsanos, E., Paliouras, G., Vouros, G.A.: Gold standard evaluation of ontology learning methods through ontology transformation and alignment. IEEE Trans. Knowl. Data Eng. 23(11), 1635–1648 (2011)

    CrossRef  Google Scholar 

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Correspondence to Alejandra Lorena Paoletti .

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Paoletti, A.L., Martinez-Gil, J., Schewe, KD. (2015). Extending Knowledge-Based Profile Matching in the Human Resources Domain. In: Chen, Q., Hameurlain, A., Toumani, F., Wagner, R., Decker, H. (eds) Database and Expert Systems Applications. Globe DEXA 2015 2015. Lecture Notes in Computer Science(), vol 9262. Springer, Cham.

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