Web-Based Semantic Similarity: An Evaluation in the Biomedical Domain

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    Computation of semantic similarity between concepts is a very common problem in many language related tasks and knowledge domains. In the biomedical field, several approaches have been developed to deal with this issue by exploiting the structured knowledge available in domain ontologies (such as SNOMED-CT or MeSH) and specific, closed and reliable corpora (such as clinical data). However, in recent years, the enormous growth of the Web has motivated researchers to start using it as the corpus to assist semantic analysis of language. This paper proposes and evaluates the use of the Web as background corpus for measuring the similarity of biomedical concepts. Several ontology-based similarity measures have been studied and tested, using a benchmark composed by biomedical terms, comparing the results obtained when applying them to the Web against approaches in which specific clinical data were used. Results show that the similarity values obtained from the Web for ontology-based measures are at least and even more reliable than those obtained from specific clinical data, showing the suitability of the Web as information corpus for the biomedical domain.

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David Sachez, Montserrat Batet, Aida Valls. Web-Based Semantic Similarity: An Evaluation in the Biomedical Domain. International Journal of Software and Informatics, 2010,4(1):39~52

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  • Received:July 15,2009
  • Revised:March 20,2010
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