Towards a semantic-based information extraction system for matching résumés to job openings
Towards a semantic-based information extraction system for matching résumés to job openings
A curriculum vitae or a r´esum´e, in general, consists of personal details, education, work experience, qualifications, and references. The overall objective of this study was to extract such data as experience, features, and business and education information from r´esum´es stored in human resources repositories. In this article, we propose an ontology-driven information extraction system that is planned to operate on several million free-format textual r´esum´es to convert them to a structured and semantically enriched version for use in semantic data mining of data essential in human resources processes. The architecture and working mechanism of the system, similarity
___
- [1] Bojars U, Breslin JG. R´esum´eRDF: expressing skill information on the semantic web. In: 1st International Workshop on ExpertFinder; 2007; Berlin, Germany.
- [2] Karamatlı E, Akyoku¸s S. R´esum´e information extraction with named entity clustering based on relationships. In: INISTA 2010 International Symposium on Innovations in Intelligent Systems and Applications; 2010; Kayseri,Turkey.
- [3] Grishman R. Information extraction techniques and challenges. In: International Summer School on Information Extraction: A Multidisciplinary Approach to an Emerging Information Technology; 1997. London, UK: LNCS. pp.1027.
- [4] Kowalkiewicz M, Kaczmarek T, Piskorski, J. Information extraction from CV. In: BIS 2005 8th International Conference on Business Information Systems; 2022 April 2005; Poznan, Poland. pp. 185189.
- [5] Sarawagi S. Information extraction. J Found Trends DBs 2008; 1: 261377.
- [6] Chieu HL, Ng HT, Lee YK. Closing the gap: learning-based information extraction rivaling. In: ACL 2003 Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics; 2003; Sapporo, Japan.
- [7] Yu K, Guan G, Zhou M. R´esum´e information extraction with cascaded hybrid model. In: ACL 2005 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics; 2005; Morristown, NJ, USA. pp. 499506.
- [8] Paolucci M. Semantic matching of Web service capabilities. In: ISWC2002 Proceedings of the 1st International Semantic Web Conference; 2002; London, UK. Berlin, Germany: Springer-Verlag. pp. 333347.
- [9] Bellur U, Vadodaria H, Gupta A. Semantic matchmaking algorithms. In: Bednorz W, editor. Advances in Greedy Algorithms. Vienna, Austria: IN-TECH Publications, 2008. pp. 481502.
- [10] Ilhan ES, Akkus GB, Bener AB. SAM: Semantic advanced matchmaker. In: SEKE 2007 19th International Conference on Software Engineering and Knowledge Engineering; 2007; Boston, MA, USA. pp. 698703.
- [11] Senvar M, Bener AB. Matchmaking of Semantic Web services using semantic-distance information. In: 4th Biennial International Conference on Advances in Information Systems; 2006. Berlin, Germany: Springer-Verlag, 2006. pp.177186.
- [12] Celik D, Elci A. Ontology-based matchmaking and composition of business processes. In: Elci A, Mamadou TK, Jack A, Orgun M, editors. Semantic Agent Systems-Foundations and Applications (SASFA) Studies in Computational Intelligence. Heidelberg, Germany: Springer-Verlag, 2011. pp. 133157.
- [13] Winkler WE. The State of Record Linkage and Current Research Problems. Technical Report. Washington, DC,USA: U.S. Census Bureau, 1999.
- [14] Winkler WE, Thibaudeau Y. An Application of the Fellegi-Sunter Model of Record Linkage to the 1990 U.S. Decennial Census. Technical Report. Washington, DC, USA: U.S. Census Bureau, 1991.
- [15] Horrocks I, Patel-Schneider P, Harold B, Tabet S, Grosof B, Dean M. SWRL: a semantic web rule language combining OWL and rule ML. In: W3C; May 2004.
- [16] Sirin E, Parsia B. Pellet: An OWL DL reasoner. In: ISWC2004 3rd International Semantic Web Conference; November 2004; Hiroshima, Japan.
- [17] Baader F, Calvanese D, McGuinness DL, Nardi D, Patel-Schneider P, editors. The Description Logic Handbook: Theory, Implementation, Applications. Cambridge, UK: Cambridge University Press, 2003.
- [18] Golbreich C, Dameron O, Bierlaire O, Gibaud B. What reasoning support for ontology and rules? The brain anatomy case study. In: OWLED 2005 Workshop on OWL: Experiences and Directions; 1112 November 2005; Ireland. pp. 311.
- [19] Horrocks I, Patel-Schneider P, Bechhofer S, Tsarkov D. OWL rules: a proposal and prototype implementation. J Web Semantics 2005; 3: 2340.
- [20] Celik D, Elci A. An ontology-based information extraction approach for r´esum´es. In: ICPCA / SWS 2012 7th International Pervasive Computing and the Networked World; 2628 October 2012. ˙Istanbul, Turkey: LNCS. pp. 45624568.