Expert Opinion Extraction from a Biomedical Database

Samet, Ahmed; Guyet, Thomas; Negrevergne, Benjamin; Dao, Tien-Tuan; Nha Hoang, Tuan; Ho Ba Tho, Marie-Christine

Samet, Ahmed; Guyet, Thomas; Negrevergne, Benjamin; Dao, Tien-Tuan; Nha Hoang, Tuan; Ho Ba Tho, Marie-Christine (2017), Expert Opinion Extraction from a Biomedical Database, dans Antonucci, Alessandro; Cholvy, Laurence; Papini, Odile, Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU), Springer : Berlin Heidelberg, p. 135-145. 10.1007/978-3-319-61581-3_13

Type

Communication / Conférence

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https://hal.inria.fr/hal-01584984

Date

2017

Titre du colloque

Symbolic and Quantitative Approaches to Reasoning with Uncertainty 14th European Conference, ECSQARU 2017, Lugano, Switzerland, July 10–14, 2017, Proceedings

Date du colloque

2017

Ville du colloque

Berlin Heidelberg

Pays du colloque

SWITZERLAND

Titre de l'ouvrage

Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU)

Auteurs de l’ouvrage

Antonucci, Alessandro; Cholvy, Laurence; Papini, Odile

Éditeur

Springer

Ville d’édition

Berlin Heidelberg

Isbn

978-3-319-61580-6

Pages

135-145

Résumé (EN)

In this paper, we tackle the problem of extracting frequent opinions from uncertain databases. We introduce the foundation of an opinion mining approach with the definition of pattern and support measure. The support measure is derived from the commitment definition. A new algorithm called OpMiner that extracts the set of frequent opinions modelled as a mass functions is detailed. Finally, we apply our approach on a real-world biomedical database that stores opinions of experts to evaluate the reliability level of biomedical data. Performance analysis showed a better quality patterns for our proposed model in comparison with literature-based methods.

Mots-clés

Uncertain database; Data mining; Opinion