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Using Biomedical Terminological Resources for Information Retrieval

Using Biomedical Terminological Resources for Information Retrieval

Piotr Pezik, Antonio Jimeno Yepes, Dietrich Rebholz-Schuhmann
Copyright: © 2009 |Pages: 20
ISBN13: 9781605662749|ISBN10: 1605662747|ISBN13 Softcover: 9781616925284|EISBN13: 9781605662756
DOI: 10.4018/978-1-60566-274-9.ch004
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MLA

Pezik, Piotr, et al. "Using Biomedical Terminological Resources for Information Retrieval." Information Retrieval in Biomedicine: Natural Language Processing for Knowledge Integration, edited by Violaine Prince and Mathieu Roche, IGI Global, 2009, pp. 58-77. https://doi.org/10.4018/978-1-60566-274-9.ch004

APA

Pezik, P., Jimeno Yepes, A., & Rebholz-Schuhmann, D. (2009). Using Biomedical Terminological Resources for Information Retrieval. In V. Prince & M. Roche (Eds.), Information Retrieval in Biomedicine: Natural Language Processing for Knowledge Integration (pp. 58-77). IGI Global. https://doi.org/10.4018/978-1-60566-274-9.ch004

Chicago

Pezik, Piotr, Antonio Jimeno Yepes, and Dietrich Rebholz-Schuhmann. "Using Biomedical Terminological Resources for Information Retrieval." In Information Retrieval in Biomedicine: Natural Language Processing for Knowledge Integration, edited by Violaine Prince and Mathieu Roche, 58-77. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-274-9.ch004

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Abstract

The present chapter discusses the use of terminological resources for Information Retrieval in the biomedical domain. The authors first introduce a number of example resources which can be used to compile terminologies for biomedical IR and explain some of the common problems with such resources including redundancy, term ambiguity, and insufficient coverage of concepts and incomplete Semantic organization of such resources for text mining purposes. They also discuss some techniques used to address each of these deficiencies, such as static polysemy detection as well as adding terms and linguistic annotation from the running text. In the second part of the chapter, the authors show how query expansion based on using synonyms of the original query terms derived from terminological resources potentially increases the recall of IR systems. Special care is needed to prevent a query drift produced by the usage of the added terms and high quality word sense disambiguation algorithms can be used to allow more conservative query expansion. In addition, they present solutions that help focus on the user’s specific information need by navigating and rearranging the retrieved documents. Finally, they explain the advantages of applying terminological and Semantic resources at indexing time. The authors argue that by creating a Semantic index with terms disambiguated for their Semantic types and larger chunks of text denoting entities and relations between them, they can facilitate query expansion, reduce the need for query refinement and increase the overall performance of Information Retrieval. Semantic indexing also provides support for generic queries for concept categories, such as genes or diseases, rather than singular keywords.

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