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Identification of concept domains and its application in biomedical information retrieval

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Abstract

With the explosive growth of biomedical information volumes, there is obviously an increasing need for developing effective and efficient tools for indexing and retrieval. Automatic indexing and retrieval in the biomedical domain is faced with several challenges such as recognition of terms denoting concepts and term disambiguation. In this paper, we are interested in identifying (sub-)domains of concepts in ontologies. We propose two algorithms for identifying the most appropriate (sub-)domain of a concept in the context of a document/query. We integrate these methods into a semantic indexing and retrieval framework. The experimental evaluation carried out on the OHSUMED collection shows that our approaches of semantic indexing and retrieval outperform the state-of-the-art approach.

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Notes

  1. In MeSH, a main heading is the preferred term denoting concepts, which can be also referred to as concept name.

  2. http://www.cismef.org/.

  3. http://sourceforge.net/projects/irtoolkit/.

  4. http://sourceforge.net/projects/cxtractor/.

  5. http://www.just-the-word.com/.

  6. http://www.natcorp.ox.ac.uk/.

  7. http://www.sketchengine.co.uk/.

  8. http://www.senseval.org/.

  9. http://biocreative.sourceforge.net/.

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  1. SANTEC Department, Public Research Center Henri Tudor, 6 Avenue des Hauts-Fourneaux, 4362, Esch-sur-Alzette, Luxembourg

    Duy Dinh

  2. IRIT Laboratory, Paul Sabatier University, 118 Route de Narbonne, 31400, Toulouse, France

    Lynda Tamine

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  1. Duy Dinh
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Dinh, D., Tamine, L. Identification of concept domains and its application in biomedical information retrieval. Inf Syst E-Bus Manage 13, 647–672 (2015). https://doi.org/10.1007/s10257-014-0259-y

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