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Knowledge Representation and Automated Methods of Searching for Information in Bibliographical Data Bases: A Rough Set Approach

  • Zbigniew Suraj
  • Piotr Grochowalski
  • Krzysztof Pancerz
Part of the Intelligent Systems Reference Library book series (ISRL, volume 43)

Abstract

In this paper, we present an approach to searching for information in bibliographical data bases founded on rough set theory and the domain knowledge. The additional knowledge of the information searched by the user is represented in the form of two kinds of ontologies: a general ontology and a specific ontology. The general ontology is built by domain experts. In research carried out, this ontology covers information about fundamental notions in the area of rough set theory and its applications as well as about significant relationships between these notions. The specific ontology delivers us the additional knowledge of a bibliographical description of a paper searched in a data base. This knowledge is extracted automatically from data gathered in the Rough Set Database System (RSDS). This system, besides a typical utility function, constitutes an environment for conducting research with a view to verify the validity of the proposed methods and algorithms devoted to searching for information in its data base.

Keywords

ontology ontological graphs rough sets database systems RSDS system 

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References

  1. 1.
    Ambroszkiewicz, S., Mikułowski, D.: Web services and semantic Web, ideas and technologies. EXIT, Warsaw (2006) (in Polish)Google Scholar
  2. 2.
    Bennacer, N., Karoui, L.: A framework for retrieving conceptual knowledge from web pages. In: Tummarello, G., Bouquet, P. (eds.) SWAP 2005 - Semantic Web Applications and Perspectives, Proceedings of the 2nd Italian Semantic Web Workshop, December 14-16. University of Trento, Trento (2005)Google Scholar
  3. 3.
    Buitelaar, P., Cimiano, P., Magnini, B.: Ontology Learning From Text: Methods, Evaluation and Applications. IOS Press (2005)Google Scholar
  4. 4.
    Corby, O., Dieng-Kuntz, R., Faron-Zucker, C.: Querying the semantic Web with corese search engine. In: Proceedings of 16th European Conference on Artificial Intelligence (ECAI/PAIS), Valencia, Spain, August 22-27, pp. 705–709. IOS Press, Amsterdam (2004)Google Scholar
  5. 5.
    Dell Orletta, F., Lenci, A., Montemagni, S., Marchi, S., Pirrelli, V., Venturi, G.: Acquiring legal ontologies from domain-specific texts. In: Proccedings of LangTech 2008, Roma, Italy, February 28-29, pp. 98–101 (2008)Google Scholar
  6. 6.
    Englmeier, K., Murtagh, F., Mothe, J.: Domain ontology: automatically extracting and structuring community language from texts. In: Proceedings of International Conference Applied Computing (IADIS), Salamanca, Spain, February 18-20, pp. 59–66 (2007)Google Scholar
  7. 7.
    Helfin, J., Hendler, J.: Searching the Web with SHOE. In: Proceedings of the AAAI Workshop on AI for Web Search, Austin, Texas, USA, July 30-August 1, pp. 35–40. AAAI Press (2000)Google Scholar
  8. 8.
    Gasperin, C., Gamallo, P., Agustini, A., Lopes, G., Lima, V.: Using syntactic contexts for measuring word similarity. In: Proceedings of the Semantic Knowledge Acquisition and Categorisation Workshop, ESSLLI 2001, Helsinki, Finland (2001)Google Scholar
  9. 9.
    Grefenstette, G.: Evaluation techniques for automatic semantic extraction: Comparing syntatic and window based approaches. In: Pustejovsky, J., Boguraev, B. (eds.) Corpus Processing for Lexical Aquisition, pp. 205–216 (1995)Google Scholar
  10. 10.
    Grochowalski, P., Pancerz, K.: The outline of an ontology for the rough set theory and its applications. Fundamenta Informaticae 93(1-3), 143–154 (2009)MathSciNetMATHGoogle Scholar
  11. 11.
    Gruber, T.R.: A translation approach to portable ontology specyfications. Knowledge Acquisition 5(2), 199–220 (1993)CrossRefGoogle Scholar
  12. 12.
    Guha, R., McCool, R., Miller, E.: Semantic search. In: Proceedings of the 12th International Conference on World Wide Web, Budapest, Hungary, May 20-24, pp. 700–709 (2003)Google Scholar
  13. 13.
    Jacob, E.K.: Ontologies and the semantic web. Bullettin of ASIST, 19–22 (2003)Google Scholar
  14. 14.
    Kłopotek, M.A.: Intelligent Search Engines. EXIT, Warsaw (2001) (in Polish)Google Scholar
  15. 15.
    Köhler, J., Philippi, S., Specht, M., Rüegg, A.: Ontology based text indexing and querying for the semantic Web. Knowledge-Based Systems 19(8), 744–754 (2006)CrossRefGoogle Scholar
  16. 16.
    Kruk, S.R., Synak, M., Zimmermann, K.: Marcont - Integration ontology for bibliographic description formats. In: Proceedings of the 2005 International Conference on Dublin Core and Metadata Applications: Vocabularies in Practice (DCMI 2005), Madrid, Spain, September 12-15, pp. 231–234 (2005)Google Scholar
  17. 17.
    Lopez, V., Pasin, M., Motta, E.: AquaLog: An Ontology-Portable Question Answering System for the Semantic Web. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 546–562. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  18. 18.
    Mittal, H., Singh, J., Sachdeva, J.: ARAGOG Semantic Search Engine: Working, Implementation and Comparison with Keyword-Based Search Engines. In: Fred, A., Dietz, J.L.G., Liu, K., Filipe, J. (eds.) IC3K 2009. CCIS, vol. 128, pp. 177–186. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  19. 19.
    Nahotko, M.: Metadata, a way of sorting the Internet out. Jagiellonian University Press, Cracow (2004) (in Polish)Google Scholar
  20. 20.
    Neches, R., Fikes, R.E., Finin, T., Gruber, T.R., Patil, R., Senator, T., Swartout, W.R.: Enabling technology for knowledge sharing. AI Magazine 12(3), 36–56 (1991)Google Scholar
  21. 21.
    Pawlak, Z.: Rough Sets. International Journal of Computer and Information Sciences 11, 341–356 (1982)MathSciNetMATHCrossRefGoogle Scholar
  22. 22.
    Pawlak, Z., Grzymała-Busse, J.W., Słowiński, R., Ziarko, W.: Rough Sets. Communications of the ACM 38(11), 88–95 (1995)CrossRefGoogle Scholar
  23. 23.
    Pawlak, Z., Skowron, A.: Rough sets and boolean reasoning. Information Sciences 177(1), 41–73 (2007)MathSciNetMATHCrossRefGoogle Scholar
  24. 24.
    Polkowski, L.T.: Rough Sets. In: Mathematical Foundations. ASC. Physica-Verlag, Heidelberg (2002)Google Scholar
  25. 25.
    Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)CrossRefGoogle Scholar
  26. 26.
    Protaziuk, G., Kryszkiewicz, M., Rybiński, H., Delteil, A.: Discovering Compound and Proper Nouns. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 505–515. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  27. 27.
    Rocha, C., Schwabe, D., de Aragao, M.P.: A hybrid approach for searching in the semantic Web. In: Proceedings of the 13th International Conference on World Wide Web, New York, USA, May 17-22, pp. 374–383 (2004)Google Scholar
  28. 28.
    Rybiński, H., Kryszkiewicz, M., Protaziuk, G., Jakubowski, A., Delteil, A.: Discovering Synonyms Based on Frequent Termsets. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 516–525. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  29. 29.
    Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Communications of the ACM 18(11), 613–620 (1975)MATHCrossRefGoogle Scholar
  30. 30.
    Skowron, A., Pal, S.K. (eds.): Special Volume: Rough Sets, Pattern Recognition and Data Mining. Pattern Recognition Letters, vol. 24(6) (2003)Google Scholar
  31. 31.
    Suraj, Z., Grochowalski, P.: The Rough Set Database System: An Overview. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 841–849. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  32. 32.
    Suraj, Z., Grochowalski, P.: Functional Extension of the RSDS System. In: Greco, S., Hata, Y., Hirano, S., Inuiguchi, M., Miyamoto, S., Nguyen, H.S., Słowiński, R. (eds.) RSCTC 2006. LNCS (LNAI), vol. 4259, pp. 786–795. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  33. 33.
    Suraj, Z., Grochowalski, P.: Patterns of collaborations in rough set research. In: Gomez, Y., Bello, R., Falcon, R. (eds.) Proceedings of the International Symposium on Fuzzy and Rough Sets, ISFUROS 2006, Santa Clara, Cuba, December 5-8 (2006)Google Scholar
  34. 34.
    Suraj, Z., Grochowalski, P., Garwol, K., Pancerz, K.: Toward intelligent searching the rough set database system (RSDS): An ontological approach. In: Szczuka, M., Czaja, L. (eds.) Proceedings of the CS&P 2009 Workshop, CS&P 2009, Krakow, September 28-30, vol. 1-2, pp. 574–582. Warsaw University, Poland (2009)Google Scholar
  35. 35.
    Velardi, P., Fabriani, P., Missikoff, M.: Using text processing techniques to automatically enrich a domain ontology. In: Proceedings of the international conference on Formal Ontology in Information Systems (FOIS 2001), pp. 270–284. ACM, New York (2001)CrossRefGoogle Scholar
  36. 36.
    Lei, Y., Uren, V.S., Motta, E.: SemSearch: A Search Engine for the Semantic Web. In: Staab, S., Svátek, V. (eds.) EKAW 2006. LNCS (LNAI), vol. 4248, pp. 238–245. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  37. 37.
    Zhou, Q., Wang, C., Xiong, M., Wang, H., Yu, Y.: SPARK: Adapting Keyword Query to Semantic Search. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 694–707. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  38. 38.
  39. 39.
    Dublin Core Metadata Initiative: DC-2005: International Conference on Dublin Core and Metadata Applications “Metadata Vocabularies in Practice”, Leganés (Madrid), Spain, September 12-15. Dublin Core Metadata Initiative (2005) http://dcpapers.dublincore.org/ojs/pubs/issue/view/28
  40. 40.
    Dublin Core Metadata Initiative: DC-2006: International Conference on Dublin Core and Metadata Applications “Metadata for Knowledge and Learning”, Manzanillo, Colima, Mexico, October 3-6. Dublin Core Metadata Initiative (2006), http://dcpapers.dublincore.org/ojs/pubs/issue/view/29
  41. 41.
    Dublin Core Metadata Initiative: DC-2008: International Conference on Dublin Core and Metadata Applications “Metadata for Semantic and Social Applications”, Berlin, Germany, September 22-26. Dublin Core Metadata Initiative (2008), http://dcpapers.dublincore.org/ojs/pubs/issue/view/32
  42. 42.
    Dublin Core Metadata Initiative: DC-2009: International Conference on Dublin Core and Metadata Applications “Semantic Interoperability of Linked Data”, Seoul, Korea, October 12-16. Dublin Core Metadata Initiative (2009), http://dcpapers.dublincore.org/ojs/pubs/issue/view/33
  43. 43.
    JeromeDL - e-library with semantics, http://www.jeromedl.org/

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Zbigniew Suraj
    • 1
  • Piotr Grochowalski
    • 1
  • Krzysztof Pancerz
    • 2
  1. 1.Institute of Computer ScienceUniversity of RzeszówRzeszówPoland
  2. 2.Institute of Biomedical InformaticsUniversity of Information Technology and ManagementRzeszówPoland

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