An increasing number of recent information retrieval systems make use of ontologies to help the users clarify their information needs and come up with semantic representations of documents. A particular concern here is the integration of these semantic approaches with traditional search technology. The research presented in this paper examines how ontologies can be efficiently applied to large-scale search systems for the web. We describe how these systems can be enriched with adapted ontologies to provide both an in-depth understanding of the user’s needs as well as an easy integration with standard vector-space retrieval systems. The ontology concepts are adapted to the domain terminology by computing a feature vector for each concept. Later, the feature vectors are used to enrich a provided query. The whole retrieval system is under development as part of a larger Semantic Web standardization project for the Norwegian oil & gas sector.


Feature Vector Information Retrieval Latent Semantic Analysis Query Term Query Expansion 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Gulla, J.A., Auran, P.G., Risvik, K.M.: Linguistic Techniques in Large-Scale Search Engines. Fast Search & Transfer 15 (2002)Google Scholar
  2. 2.
    Spink, A., Wolfram, D., Jansen, M.B.J., Saracevic, T.: Searching the Web: the public and their queries. J. Am. Soc. Inf. Sci. Technol. 52, 226–234 (2001)CrossRefGoogle Scholar
  3. 3.
    Grootjen, F.A., van der Weide, T.P.: Conceptual query expansion. Data & Knowledge Engineering 56, 174–193 (2006)CrossRefGoogle Scholar
  4. 4.
    Qiu, Y., Frei, H.-P.: Concept based query expansion. In: Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 160–169. ACM Press, Pittsburgh (1993)CrossRefGoogle Scholar
  5. 5.
    Chang, Y., Ounis, I., Kim, M.: Query reformulation using automatically generated query concepts from a document space. Information Processing and Management 42, 453–468 (2006)CrossRefGoogle Scholar
  6. 6.
    Gruber, T.R.: A translation approach to portable ontology specifications. Knowledge Acquisition 5, 199–220 (1993)CrossRefGoogle Scholar
  7. 7.
    Tomassen, S.L., Gulla, J.A., Strasunskas, D.: Document Space Adapted Ontology: Application in Query Enrichment. In: 11th International Conference on Applications of Natural Language to Information Systems. Springer, Klagenfurt (2006)Google Scholar
  8. 8.
    Desmontils, E., Jacquin, C.: Indexing a Web Site with a Terminology Oriented Ontology. In: Cruz, I.F., Decker, S., Euzenat, J., McGuinness, D.L. (eds.) The Emerging Semantic Web, pp. 181–198. IOS Press, Amsterdam (2002)Google Scholar
  9. 9.
    Motta, E., Shum, S.B., Domingue, J.: Case Studies in Ontology-Driven Document Enrichment: Principles, Tools and Applications. International Journal of Human-Computer Studies 6, 1071–1109 (2000)CrossRefGoogle Scholar
  10. 10.
    Popov, B., Kiryakov, A., Kirilov, A., Manov, D., Ognyanoff, D., Goranov, M.: KIM - Semantic Annotation Platform. In: Fensel, D., Sycara, K.P., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 834–849. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  11. 11.
    Fensel, D., Harmelen, F.v., Klein, M., Akkermans, H., Broekstra, J., Fluit, C., Meer, J.v.d., Schnurr, H.-P., Studer, R., Hughes, J., Krohn, U., Davies, J., Engels, R., Bremdal, B., Ygge, F., Lau, T., Novotny, B., Reimer, U., Horrocks, I.: On-To-Knowledge: Ontology-based Tools for Knowledge Management. In: Proceedings of the eBusiness and eWork 2000 (EMMSEC 2000) Conference, Madrid, Spain (2000)Google Scholar
  12. 12.
    Sullivan, D.: Death of a Meta Tag. Search Engine Watch (2002)Google Scholar
  13. 13.
    Song, J.-F., Zhang, W.-M., Xiao, W., Li, G.-H., Xu, Z.-N.: Ontology-Based Information Retrieval Model for the Semantic Web. In: Proceedings of EEE 2005, pp. 152–155. IEEE Computer Society, Los Alamitos (2005)Google Scholar
  14. 14.
    Rocha, C., Schwabe, D., de Aragao, M.P.: A hybrid approach for searching in the semantic web. In: Proceeding of WWW 2004, pp. 374–383. ACM, New York (2004)CrossRefGoogle Scholar
  15. 15.
    Ciorăscu, C., Ciorăscu, I., Stoffel, K.: knOWLer - Ontological Support for Information Retrieval Systems. In: Proceedings of Sigir 2003 Conference, Workshop on Semantic Web, Toronto, Canada (2003)Google Scholar
  16. 16.
    Kiryakov, A., Popov, B., Terziev, I., Manov, D., Ognyanoff, D.: Semantic Annotation, Indexing, and Retrieval. Journal of Web Semantics 2(1) (2005)Google Scholar
  17. 17.
    Braga, R.M.M., Werner, C.M.L., Mattoso, M.: Using Ontologies for Domain Information Retrieval. In: Proceedings of the 11th International Workshop on Database and Expert Systems Applications, pp. 836–840. IEEE Computer Society, Los Alamitos (2000)CrossRefGoogle Scholar
  18. 18.
    Borghoff, U.M., Pareschi, R.: Information Technology for Knowledge Management. Journal of Universal Computer Science 3, 835–842 (1997)zbMATHGoogle Scholar
  19. 19.
    Shah, U., Finin, T., Joshi, A., Cost, R.S., Mayfield, J.: Information Retrieval On The Semantic Web. In: Proceedings of Conference on Information and Knowledge Management, pp. 461–468. ACM Press, McLean (2002)Google Scholar
  20. 20.
    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
  21. 21.
    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
  22. 22.
    Paralic, J., Kostial, I.: Ontology-based Information Retrieval. Information and Intelligent Systems, Croatia, 23–28 (2003)Google Scholar
  23. 23.
    Chenggang, W., Wenpin, J., Qijia, T., et al.: An information retrieval server based on ontology and multiagent. Journal of computer research & development 38(6), 641–647 (2001)Google Scholar
  24. 24.
    Ozcan, R., Aslangdogan, Y.A.: Concept Based Information Access Using Ontologies and Latent Semantic Analysis. Technical Report CSE-2004-8. University of Texas at Arlington, p. 16 (2004)Google Scholar
  25. 25.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern information retrieval. ACM Press, New York (1999)Google Scholar
  26. 26.
    Tomassen, S.L., Strasunskas, D.: Query Terms Abstraction Layers. In: Web Semantics (SWWS 2006) in conjunction with OnTheMove Federated Conferences (OTM 2006), Montpellier, France (Submitted, 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Stein L. Tomassen
    • 1
  1. 1.Department of Computer and Information ScienceNorwegian University of Technology and ScienceTrondheimNorway

Personalised recommendations