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Biomedical Concepts Extraction Based on Possibilistic Network and Vector Space Model

  • Wiem ChebilEmail author
  • Lina Fatima Soualmia
  • Mohamed Nazih Omri
  • Stéfan Jacques Darmoni
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9105)

Abstract

This paper proposes a new approach for indexing biomedical documents based on the combination of a Possibilistic Network and a Vector Space Model. This later carries out partial matching between documents and biomedical vocabularies. The main contribution of the proposed approach is to combine the cosine similarity and the two measures of possibility and necessity to enhance the estimation of the similarity between a document and a given concept. The possibility estimates the extent to which a document is not similar to the concept. The necessity allows the confirmation that the document is similar to the concept. Experiments were carried out on the OSHUMED corpora and showed encouraging results.

Keywords

Indexing Biomedical documents Possibilistic network Vector space model Partial matching 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Wiem Chebil
    • 1
    • 2
    Email author
  • Lina Fatima Soualmia
    • 1
    • 3
  • Mohamed Nazih Omri
    • 2
  • Stéfan Jacques Darmoni
    • 1
    • 3
  1. 1.LITIS-TIBS EA 4108Normandie University, Rouen University and HospitalRouenFrance
  2. 2.Research unit MARSMonastir UniversityMonastirTunisia
  3. 3.French National Institute for Health, INSERM, LIMICS UMR 1142ParisFrance

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