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dc.contributor.authorMansour, Elioen_US
dc.contributor.authorTekli, Gilberten_US
dc.contributor.authorArnould, Philippeen_US
dc.contributor.authorChbeir, Richarden_US
dc.contributor.authorCardinale, Yudithen_US
dc.description.abstractIn the context of social media, existent works offer social-event-based organization of multimedia objects (e.g., photos, videos) by mainly considering spatio-temporal data, while neglecting other user-related information (e.g., people, user interests). In this paper we propose an automated, extensible, and incremental Feature-centric Social Event Detection (F-SED) approach, based on Formal Concept Analysis (FCA), to organize shared multimedia objects on social media platforms and sharing applications. F-SED simultaneously considers various event features (e.g., temporal, geographical, social (user related)), and uses the latter to detect different feature-centric events (e.g., user-centric, location-centric). Our experimental results show that detection accuracy is improved when, besides spatio-temporal information, other features, such as social, are considered. We also show that the performance of our prototype is quasi-linear in most cases.en_US
dc.format.extent17 p.en_US
dc.subjectSocial Event Detectionen_US
dc.subjectSemantic clusteringen_US
dc.subjectMultimedia sharingen_US
dc.subjectFormal Concept Analysisen_US
dc.subject.lcshSocial networksen_US
dc.titleF-SED : Feature-Centric Social Event Detectionen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Database and Expert Systems Applications (28-31 August 2017 : Lyon, France)en_US
dc.contributor.affiliationDepartment of Mechatronics Engineeringen_US
dc.relation.ispartoftextDatabase and Expert Systems Applications : 28th International Conference, DEXA 2017, Lyon, France, August 28-31, 2017, Proceedings, Part IIen_US
dc.provenance.recordsourceOliben_US Fares Faculty of Technology-
Appears in Collections:Department of Mechatronics Engineering
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