A Method of Automatic Detection of Lexical Relationships Using a Raw Corpus

  • Héctor Jiménez-Salazar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2588)


This work presents some results on the application of a criterion used to compare the senses of a pair of words. A measure that involves the senses of words was used to reinforce hypothesis like hyponymy relationship between the words.


Query Expansion Word Sense Information Retrieval System Index Term Concept Hierarchy 
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.
    Davey, B. amp; Priestley, H.: Introduction to lattices and order, Cambridge Mathematical Textbooks, 1990.Google Scholar
  2. 2.
    Gelbukh, A.: Lazy query enrichment: a simple method of indexing large specialized document bases, Proc.DEXA-2000 11th Int. Conf. and Workshop on Databases and Expert Systems Applications, 2000.Google Scholar
  3. 3.
    Lavalle-Martínez, J.: Representación isoanalógica de objetos n-dimensionales, M.Sc. Thesis, CINVESTAV (México), 2000.Google Scholar
  4. 4.
    Mandala, R.; Tokunaga, T. amp; Tanaka, H.: Combining multiple evidence from different types of thesaurus, Proc. 22nd International Conference ACM-SIGIR, 191–197, 1999.Google Scholar
  5. 5.
    Salton, G.; Yang, C.S. amp; Yu, C.T.: A theory of term importance in automatic text analysis, Journal of American Society for Information Science, 26(1), 33–44, 1975.CrossRefGoogle Scholar
  6. 6.
    Sanderson, M. amp; Croft, W.B.: Deriving concept hierarchies from text, Proc. 22nd International Conference ACM-SIGIR, 206–213, 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Héctor Jiménez-Salazar
    • 1
  1. 1.Facultad de Ciencias de la ComputaciónB. Universidad Autónoma de PueblaPueblaMéxico

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