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|Title:||F-SED : Feature-Centric Social Event Detection||Authors:||Mansour, Elio
|Affiliations:||Department of Mechatronics Engineering||Keywords:||Social Event Detection
Formal Concept Analysis
|Subjects:||Social networks||Issue Date:||2017||Publisher:||Springer||Part of:||Database and Expert Systems Applications : 28th International Conference, DEXA 2017, Lyon, France, August 28-31, 2017, Proceedings, Part II||Start page:||409||End page:||426||Conference:||International Conference on Database and Expert Systems Applications (28-31 August 2017 : Lyon, France)||Abstract:||
In 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.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/552||Ezproxy URL:||Link to full text||Type:||Conference Paper|
|Appears in Collections:||Department of Mechatronics Engineering|
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