Document (#30283)

Author
Freitas-Junior, H.R.
Ribeiro-Neto, B.A.
Freitas-Vale, R. de
Laender, A.H.F.
Lima, L.R.S. de
Title
Categorization-driven cross-language retrieval of medical information
Source
Journal of the American Society for Information Science and Technology. 57(2006) no.4, S.501-510
Year
2006
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.
Theme
Multilinguale Probleme
Field
Medizin

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  4. Qin, J.; Zhou, Y.; Chau, M.; Chen, H.: Multilingual Web retrieval : an experiment in English-Chinese business intelligence (2006) 0.47
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  5. Dadashkarimia, J.; Shakery, A.; Failia, H.; Zamani, H.: ¬An expectation-maximization algorithm for query translation based on pseudo-relevant documents (2017) 0.44
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