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A Model for Generating Related Weighted Boolean Queries

  • Jesus Serrano-Guerrero
  • Jose A. Olivas
  • Enrique Herrera-Viedma
  • Francisco P. Romero
  • Jose Ruiz-Morilla
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6098)

Abstract

In this paper a model for polyrepresenting weighted boolean queries based on reformulation is presented. This model tries to generate a set of boolean queries for completing the meaning of the original query instead of modifying the query adding, changing or removing terms as techniques such as query expansion propose. This model is specially designed for those systems which do not support very large queries such as the Web search engines.

The input of the model are boolean queries which have been weighted by the user in order to express some semantics that the set of polyrepresented queries have to satisfy. The user is able to fix a threshold for limiting the minimum resemblance of the polyrepresented queries and the original one. From the original query, using a reformulation strategy which guarantees that length of the new queries is not enlarged excessively, the proposed model generates a set of candidate queries/concepts for representing the original one. That set is reduced by a bottom-up process based on the semantics established by the user in order to choose the best queries for representing the original one.

Keywords

Query polyrepresentation Weighted boolean queries Fuzzy logic 

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References

  1. 1.
    Belkin, N.J., Kantor, P., Fox, E.A., Shaw, J.A.: Combining the evidence of multiple query representations for information retrieval. Information Processing and Management 31, 431–448 (1995)CrossRefGoogle Scholar
  2. 2.
    Bordogna, G., Carrara, P., Pasi, G.: Query term weights as constraints in fuzzy information retrieval. Information Processing and Management 27, 15–26 (1991)CrossRefGoogle Scholar
  3. 3.
    Bruza, P., Dennis, S.: Query Reformulation on the Internet: Empirical Data and the Hyperindex Search Engine. In: Proceedings of RIAO ’97 - Computer Assisted Information Searching on the Internet, pp. 500–509 (1997)Google Scholar
  4. 4.
    Efthimiadis, E.N.: A user-centred evaluation of ranking algorithms for interactive query expansion. In: SIGIR ’93: Proceedings of the 16th annual international ACM SIGIR conference, New York, NY, USA, pp. 146–159 (1993)Google Scholar
  5. 5.
    Grootjen, F.A., Van Der Weide, T.P.: Conceptual query expansion. Data and Knowledge Engineering 56, 174–193 (2006)CrossRefGoogle Scholar
  6. 6.
    Herrera-Viedma, E.: Modeling the retrieval process for an information retrieval system using an ordinal fuzzy linguistic approach. Journal of the American Society for Information Science and Technology 52, 460–475 (2001)CrossRefGoogle Scholar
  7. 7.
    Ingwersen, P., Jarvelin, K.: The Turn: Integration of Information Seeking and Retrieval in Context. Springer, Secaucus (2005)zbMATHGoogle Scholar
  8. 8.
    Jansen, B.J., Booth, D.L., Spink, A.: Patterns of query reformulation during Web searching. Journal of the American Society for Information Science and Technology 60, 1358–1371 (2009)CrossRefGoogle Scholar
  9. 9.
    Jansen, B.J., Spink, A.: An analysis of web searching by European AlltheWeb.com users. Information Processing and Management 41, 361–381 (2005)CrossRefGoogle Scholar
  10. 10.
    Jarvelin, K., Kekalainen, J., Niemi, T.: ExpansionTool: Concept-Based Query Expansion and Construction. Information Retrieval 4, 231–255 (2001)CrossRefGoogle Scholar
  11. 11.
    Kekalainen, J., Jarvelin, K.: The Co-Effects of Query Structure and Expansion on Retrieval Performance in Probabilistic Text Retrieval. Information Retrieval 1, 329–344 (2000)CrossRefGoogle Scholar
  12. 12.
    Rieh, S.Y., Xie, H.: Analysis of multiple query reformulations on the web: The interactive information retrieval context. Information Processing and Management 42, 751–768 (2006)CrossRefGoogle Scholar
  13. 13.
    Saracevic, T., Kantor, P.: A study of information seeking and retrieving. III. Searchers, searches and overlap. Journal of the American Society for Information Science 3, 197–216 (1988)CrossRefGoogle Scholar
  14. 14.
    Serrano-Guerrero, J., Romero, F.P., Olivas, J.A., De La Mata, J., Soto, A.: BUDI: Architecture for Fuzzy Search in Documental Repositories. Mathware and Soft Computing 16, 71–85 (2009)zbMATHGoogle Scholar
  15. 15.
    Skov, M., Larsen, B., Ingwersen, P.: Inter and intra-document contexts applied in polyrepresentation for best match IR. Information Processing and Management 44, 1673–1683 (2008)CrossRefGoogle Scholar
  16. 16.
    Xu, J., Croft, B.W.: Improving the effectiveness of information retrieval with local context analysis. ACM Transactions on Information Systems 18, 79–112 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jesus Serrano-Guerrero
    • 1
    • 2
  • Jose A. Olivas
    • 1
    • 2
  • Enrique Herrera-Viedma
    • 1
    • 2
  • Francisco P. Romero
    • 1
    • 2
  • Jose Ruiz-Morilla
    • 1
    • 2
  1. 1.Department of Information Technologies and SystemsUniversity of Castilla-La ManchaCiudad RealSpain
  2. 2.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain

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