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F-SED: Feature-Centric Social Event Detection

  • Elio MansourEmail author
  • Gilbert Tekli
  • Philippe Arnould
  • Richard Chbeir
  • Yudith Cardinale
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10439)

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.

Keywords

Social Event Detection Social networks Semantic clustering Multimedia sharing Formal Concept Analysis 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Elio Mansour
    • 1
    Email author
  • Gilbert Tekli
    • 3
  • Philippe Arnould
    • 1
  • Richard Chbeir
    • 2
  • Yudith Cardinale
    • 4
  1. 1.University Pau & Pays Adour, LIUPPA, EA3000Mont De MarsanFrance
  2. 2.University Pau & Pays Adour, LIUPPA, EA3000AngletFrance
  3. 3.University of BalamandSouk El GharebLebanon
  4. 4.Dept. de ComputaciónUniversidad Simón BolívarCaracasVenezuela

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