Categorization-driven cross-language retrieval of medical information

  • Authors:
  • Hermes R. Freitas-Junior;Berthier Ribeiro-Neto;Rodrigo F. Vale;Alberto H. F. Laender;Luciano R. S. Lima

  • Affiliations:
  • Google Brazil, Av. Antônio Abraão Caram, 430, Zip 31275-000, Belo Horizonte, MG, Brazil;Akwan Information Technologies, Av. Antônio Abrão Caram, 430, Zip 31275-000, Belo Horizonte and Dept. of Comp. Sci., Fed. Univ. of Minas Gerais, Av. Antônio Carlos, 6627, Zip 31270- ...;Google Brazil, Av. Antônio Abrão Caram, 430, Zip 31275-000, Belo Horizonte, MG, Brazil;Department of Computer Science, Federal University of Minas Gerais, Av. Antônio Carlos, 6627, Zip 31270-901, Belo Horizonte, MG, Brazil;Department of Computer Science, Federal University of Minas Gerais and The Sarah Network of Hospitals for Rehabilitation, Av. Amazonas, 5953, Zip 30510-000, Belo Horizonte, MG, Brazil

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2006

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Abstract

The Web has become a large repository of documents (or pages) written in many different languages. In this context, traditional information retrieval (IR) techniques cannot be used whenever the user query and the documents being retrieved are in different languages. To address this problem, new cross-language information retrieval (CLIR) techniques have been proposed. In this work, we describe a method for cross-language retrieval of medical information. This method combines query terms and related medical concepts obtained automatically through a categorization procedure. The medical concepts are used to create a linguistic abstraction that allows retrieval of information in a language-independent way, minimizing linguistic problems such as polysemy. To evaluate our method, we carried out experiments using the OHSUMED test collection, whose documents are written in English, with queries expressed in Portuguese, Spanish, and French. The results indicate that our cross-language retrieval method is as effective as a standard vector space model algorithm operating on queries and documents in the same language. Further, our results are better than previous results in the literature. © 2006 Wiley Periodicals, Inc.