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Ontology Supported Automatic Generation of High-Quality Semantic Metadata

  • Ümit Yoldas
  • Gábor Nagypál
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4275)

Abstract

Large amounts of data in modern information systems, such as the World Wide Web, require innovative information retrieval techniques to effectively satisfy users’ information need. A promising approach is to exploit document semantics in the IR process. For this purpose, high-quality semantic metadata is needed. This paper introduces a method to automatically create semantic metadata by using ontologically enhanced versions of common information extraction methods, such as named entity recognition and coreference resolution. Furthermore, this work also proposes the application of ontology-specific heuristic rules to further improve the quality of generated metadata. The results of our method was evaluated using a small test collection.

Keywords

Vector Space Model Heuristic Rule Information Retrieval System Name Entity Recognition Name Entity 
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.

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References

  1. 1.
    Nagypál, G.: Improving information retrieval effectiveness by using domain knowledge stored in ontologies. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM-WS 2005. LNCS, vol. 3762, pp. 780–789. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Voorhees, E.M.: Using WordNet to disambiguate word sense for text retrieval. In: Proceedings of SIGIR 1993, 16th ACM International Conference on Research and Development in Information Retrieval, Pittsburgh, US, pp. 171–180 (1993)Google Scholar
  3. 3.
    Gruber, T.: A translation approach to portable ontology specifications. Knowledge Acquisition 5, 199–220 (1993); the definition of the word ”ontology”CrossRefGoogle Scholar
  4. 4.
    Dean, M., Schreiber, G.: OWL web ontology language reference. Recommendation, W3C (2004)Google Scholar
  5. 5.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284, 34–43 (2001)CrossRefGoogle Scholar
  6. 6.
    Decker, S., Erdmann, M., Fensel, D., Studer, R.: Ontobroker: Ontology based access to distributed and semi-structured information. In: Meersman, R., Tari, Z., Stevens, S.M. (eds.) Database Semantics - Semantic Issues in Multimedia Systems, IFIP TC2/WG2.6 Eighth Working Conference on Database Semantics (DS-8). IFIP Conference Proceedings, vol. 138, pp. 351–369. Kluwer, Dordrecht (1999)Google Scholar
  7. 7.
    Handschuh, S., Staab, S., Ciravegna, F.: S-CREAM – semi-automatic cREAtion of metadata. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS, vol. 2473, pp. 358–372. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  8. 8.
    Hendler, J., Heflin, J.: Searching the web with SHOE. In: Artificial Intelligence for Web Search. Papers from the AAAI Workshop, pp. 35–40. AAAI Press, Menlo Park (2000)Google Scholar
  9. 9.
    Martin, P., Eklund, P.: Embedding knowledge in web documents. In: Proceedings of the Eighth International World Wide Web Conference, Toronto, Canada, pp. 325–341. Elsevier, Amsterdam (1999)Google Scholar
  10. 10.
    Nagypál, G., Deswarte, R., Oosthoek, J.: Applying the Semantic Web – the VICODI experience in creating visual contextualization for history. Literary and Linguistic Computing 20, 327–349 (2005)CrossRefGoogle Scholar
  11. 11.
    Hustadt, U., Motik, B., Sattler, U.: Reducing SHIQ-description logic to disjunctive datalog programs. In: Principles of Knowledge Representation and Reasoning: Proceedings of the Ninth International Conference (KR2004), pp. 152–162 (2004)Google Scholar
  12. 12.
    Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Communications of the ACM 18, 613–620 (1975)zbMATHCrossRefGoogle Scholar
  13. 13.
    Finin, T., Mayfield, J., Joshi, A., Cost, R.S., Fink, C.: Information retrieval and the Semantic Web. In: Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS 2005) (2005)Google Scholar
  14. 14.
    Kiryakov, A., Popov, B., Terziev, I., Manov, D., Ognyanoff, D.: Semantic annotation, indexing, and retrieval. Journal of Web Semantics 2, 49–79 (2005)CrossRefGoogle Scholar
  15. 15.
    Davies, J., Weeks, R.: QuizRDF: Search technology for the Semantic Web. In: Proceedings of the 37th Hawaii International Conference on System Sciences (HICSS-37 2004) (2004)Google Scholar
  16. 16.
    Nagypál, G., Motik, B.: A fuzzy model for representing uncertain, subjective, and vague temporal knowledge in ontologies. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) CoopIS 2003, DOA 2003, and ODBASE 2003. LNCS, vol. 2888, pp. 906–923. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  17. 17.
    Vallet, D., Fernández, M., Castells, P.: An ontology-based information retrieval model. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 455–470. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  18. 18.
    Kahan, J., Koivunen, M.R., Prud’Hommeaux, E., Swick, R.R.: Annotea: An open RDF infrastructure for shared web annotations. Computer Networks 39, 589–608 (2002)CrossRefGoogle Scholar
  19. 19.
    Dill, S., Eiron, N., Gibson, D., Gruhl, D., Guha, R., Jhingran, A., Kanungo, T., Rajagopalan, S., Tomkins, A., Tomlin, J.A., Zien, J.Y.: SemTag and Seeker: Bootstrapping the semantic web via automated semantic annotation. In: Proceedings of the Twelfth International World Wide Web Conference, WWW 2003, Budapest, Hungary, pp. 178–186 (2003)Google Scholar
  20. 20.
    Cimiano, P., Ladwig, G., Staab, S.: Gimme’ the context: context-driven automatic semantic annotation with C-PANKOW. In: Ellis, A., Hagino, T. (eds.) Proceedings of the 14th international conference on World Wide Web, WWW 2005, Chiba, Japan, pp. 332–341. ACM, New York (2005)CrossRefGoogle Scholar
  21. 21.
    Rocha, C., Schwabe, D., Aragao, M.P.: A hybrid approach for searching in the semantic web. In: Proceedings of the 13th international conference on World Wide Web (WWW 2004), pp. 374–383. ACM Press, New York (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ümit Yoldas
    • 1
  • Gábor Nagypál
    • 2
  1. 1.Conemis AGKarlsruheGermany
  2. 2.FZI Research Center for Information Technologies, at the University of KarlsruheKarlsruheGermany

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