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, in 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

External document link

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

Date

2017

Conference title

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

Conference date

2017

Conference city

Berlin Heidelberg

Conference country

SWITZERLAND

Book title

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

Book author

Antonucci, Alessandro; Cholvy, Laurence; Papini, Odile

Publisher

Springer

Published in

Berlin Heidelberg

ISBN

978-3-319-61580-6

Pages

135-145

Abstract (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.

Subjects / Keywords

Uncertain database; Data mining; Opinion