Sesei: A CG-Based Filter for Internet Search Engines

  • Stéphane Nicolas
  • Bernard Moulin
  • Guy W. Mineau
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2746)


The web faces a major contradiction: it has been created to present information to human beings but the increase of available information sources on the web makes it more difficult for people to find the most relevant documents when browsing through numerous pages of URLs returned by search engines. Classic indexing and retrieval techniques have an important limitation: the retrieved documents do not necessarily match the meaning of the user’s query. In order to address this issue, we designed a system capable of matching conceptual structures extracted from both the user’s query and documents retrieved by a classic search engine like Google. This article presents our fully functional application and provides details about its behavior. The application provides a new framework for broader experiments in the manipulation of conceptual structures extracted from natural language documents and is built upon research and tools developped by the CG community.


Syntactic Structure Conceptual Structure Query Graph Conceptual Graph Concept Type 
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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  1. 1.
    Barrière, C.: From a Children’s First Dictionary to a Lexical Knowledge Base of Conceptual Graphs. PhD thesis, Université Simon Fraser (1997)Google Scholar
  2. 2.
    Mel’čuk, I.: Leçon inaugurale. Collège de France, Chaire Internatonale (1997),
  3. 3.
    Järvinen, T., Tapanainen, P.: Towards an implementable dependency grammar (1998),
  4. 4.
    Montes-y Gómez, M.: Minería de texto empleando la semenjanza entre estructuras semánticas. PhD thesis, Centro de Investigación en Computación, Instituto Polit’ecnico Nacional, Mexíco (2002)Google Scholar
  5. 5.
    Montes-y Gómez, M., Gelbukh, A., López López, A.: Flexible Comparison of Conceptual Graphs. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, p. 102. Springer, Heidelberg (2001),
  6. 6.
    Nicolas, S., Moulin, B., Mineau, G.: Extracting Conceptual Structures from English Texts Using a Lexical Ontology and a Grammatical Parser. In: Sup. Proc. of 10th International Conference on Conceptual Structures, ICCS 2002 (2002),
  7. 7.
    Poole, J., Campbell, J.A.: A Novel Algorithm for Matching Conceptual and Related Graphs. In: Proceedings of ICCS 1995 (1995)Google Scholar
  8. 8.
    Roux, C., Proux, D., Rechennmann, F., Julliard, L.: An Ontology Enrichment Method for a Pragmatic Information Extraction System gathering Data on Genetic Interactions,
  9. 9.
    Southey, F., Linders, J.G.: Notio - A Java API for Developing CG Tools. In: Tepfenhart, W.M. (ed.) ICCS 1999. LNCS, vol. 1640, pp. 262–271. Springer, Heidelberg (1999), CrossRefGoogle Scholar
  10. 10.
    Sowa, J.F., Way, E.C.: Implementing a semantic interpreter using conceptual graphs. IBM Journal of Research and Development (1986)Google Scholar
  11. 11.
    Tajarobi, A.: La reconnaissance automatique des hyponymes. Master’s thesis, Département de langues et linguistique, Université Laval (1998)Google Scholar
  12. 12.
    Tesnière, L.: Eléments de syntaxe structurale. Editions Klincksieck, Paris (1959)Google Scholar
  13. 13.
    Zhong, J., Zhu, H., Li, J., Yu, Y.: Conceptual Graph Matching for Semantic Search. In: Priss, U., Corbett, D.R., Angelova, G. (eds.) ICCS 2002. LNCS (LNAI), vol. 2393, pp. 93–106. Springer, Heidelberg (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Stéphane Nicolas
    • 1
  • Bernard Moulin
    • 1
  • Guy W. Mineau
    • 1
  1. 1.Université Laval, QuébecQuébecCanada

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