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A Conceptual Model for Word Sense Disambiguation in Medical Image Retrieval

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 8281)

Abstract

Word sense disambiguation (WSD) is the task of determining the meaning of an ambiguous word. It is an open problem in natural language processing because effective WSD can improve the quality of related fields such as information retrieval. Although WSD systems achieve sufficiently high levels of accuracy thanks to several technologies, it remains a challenging problem in the medical domain. In this paper, we propose a conceptual model to resolve the word sens ambiguity problem using the semantic relations between extracted concepts, through MetaMap tool and UMLS Metathesaurus. The evaluation of our disambiguation model is done through the use of information retrieval domain. Results carried out with Clef medical image retrieval 2009 show that our WSD model improves the results that are obtained by the MetaMap WSD model.

Keywords

  • medical image retrieval
  • semantic graph
  • word sense disambiguation and concept mapping

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Gasmi, K., Torjmen Khemakhem, M., Ben Jemaa, M. (2013). A Conceptual Model for Word Sense Disambiguation in Medical Image Retrieval. In: Banchs, R.E., Silvestri, F., Liu, TY., Zhang, M., Gao, S., Lang, J. (eds) Information Retrieval Technology. AIRS 2013. Lecture Notes in Computer Science, vol 8281. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45068-6_26

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  • DOI: https://doi.org/10.1007/978-3-642-45068-6_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-45067-9

  • Online ISBN: 978-3-642-45068-6

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