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Expert Opinion Extraction from a Biomedical Database

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
Publication identifier
Metadata
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Author(s)
Samet, Ahmed
Guyet, Thomas
Negrevergne, Benjamin cc
Dao, Tien-Tuan cc
Nha Hoang, Tuan
Ho Ba Tho, Marie-Christine
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