Indexing biomedical documents with a possibilistic network

Wiem Chebil 1, 2 Lina Fatima Soualmia 1, 2 Mohamed Nazih Omri 3 Stéfan Jacques Darmoni 1, 2
1 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes
2 TIBS - LITIS - Equipe Traitement de l'information en Biologie Santé
LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes
3 Faculté des Sciences de Monastir
Abstract : In this article, we propose a new approach for indexing biomedical documents based on a possibilistic network that carries out partial matching between documents and biomedical vocabulary. The main contribution of our approach is to deal with the imprecision and uncertainty of the indexing task using possibility theory. We enhance estimation of the similarity between a document and a given concept using the two measures of possibility and necessity. Possibility estimates the extent to which a document is not similar to the concept. The second measure can provide confirmation that the document is similar to the concept. Our contribution also reduces the limitation of partial matching. Although the latter allows extracting from the document other variants of terms than those in dictionaries, it also generates irrelevant information. Our objective is to filter the index using the knowledge provided by the Unified Medical Language System®. Experiments were carried out on different corpora, showing encouraging results (the improvement rate is +26.37% in terms of main average precision when compared with the baseline).
Keywords : indexing semantics uncertainty
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Article dans une revue
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https://hal-normandie-univ.archives-ouvertes.fr/hal-02100414
Contributeur : Lina F Soualmia <>
Soumis le : lundi 15 avril 2019 - 19:21:10
Dernière modification le : jeudi 12 décembre 2019 - 14:12:08

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COMUE-NORMANDIE | LITIS | INSA-ROUEN | UNIROUEN | UNILEHAVRE | INSA-GROUPE

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Wiem Chebil, Lina Fatima Soualmia, Mohamed Nazih Omri, Stéfan Jacques Darmoni. Indexing biomedical documents with a possibilistic network. Journal of the Association for Information Science and Technology, ASIS&T/Wiley, 2016, 67 (4), pp.928-941. ⟨10.1002/asi.23435⟩. ⟨hal-02100414⟩

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