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Ontology-Based Text Classification for Filtering Cholangiocarcinoma Documents from PubMed

  • Chumsak Sibunruang
  • Jantima Polpinij
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8609)

Abstract

PubMed is a search engine used to access the MEDLINE database, which comprises the massive amounts of biomedical literature. This an make more difficult for accessing to find the relevant medical literature. Therefore, this problem has been challenging in this work. We present a solution to retrieve the most relevant biomedical literature relating to Cholangiocarcinoma in clinical trials from PubMed. The proposed methodology is called ontology-based text classification (On-TC). We provide an ontology used as a semantic tool. It is called Cancer Technical Term Net (CCT-Net). This ontology is intergrated to the methodology to support automatic semantic interpretation during text processing, especially in the case of synonyms or term variations.

Keywords

PubMed Ontology CCT-Net Text Classification Cholangiocarcinoma 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Chumsak Sibunruang
    • 1
  • Jantima Polpinij
    • 1
  1. 1.Intellect Laboratory, Faculty of InformaticsMahasarakham UniversityMahasarakhamThailand

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