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dc.contributor.authorSamet, Ahmed
dc.contributor.authorGuyet, Thomas
dc.contributor.authorNegrevergne, Benjamin
dc.contributor.authorDao, Tien-Tuan
dc.contributor.authorNha Hoang, Tuan
dc.contributor.authorHo Ba Tho, Marie-Christine
dc.date.accessioned2020-09-29T16:03:07Z
dc.date.available2020-09-29T16:03:07Z
dc.date.issued2017
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/21015
dc.language.isoenen
dc.subjectUncertain database
dc.subjectData mining
dc.subjectOpinion
dc.subject.ddc005.7en
dc.titleExpert Opinion Extraction from a Biomedical Database
dc.typeCommunication / Conférence
dc.description.abstractenIn 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.
dc.identifier.citationpages135-145
dc.relation.ispartoftitleConference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU)
dc.relation.ispartofeditorAntonucci, Alessandro
dc.relation.ispartofeditorCholvy, Laurence
dc.relation.ispartofeditorPapini, Odile
dc.relation.ispartofpublnameSpringer
dc.relation.ispartofpublcityBerlin Heidelberg
dc.relation.ispartofurl10.1007/978-3-319-61581-3
dc.identifier.urlsitehttps://hal.inria.fr/hal-01584984
dc.subject.ddclabelOrganisation des donnéesen
dc.relation.ispartofisbn978-3-319-61580-6
dc.relation.conftitleSymbolic and Quantitative Approaches to Reasoning with Uncertainty 14th European Conference, ECSQARU 2017, Lugano, Switzerland, July 10–14, 2017, Proceedings
dc.relation.confdate2017
dc.relation.confcityBerlin Heidelberg
dc.relation.confcountrySWITZERLAND
dc.relation.forthcomingnonen
dc.identifier.doi10.1007/978-3-319-61581-3_13
dc.description.ssrncandidatenon
dc.description.halcandidatenon
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2020-11-04T11:04:55Z
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