Towards BOTTARI: Using Stream Reasoning to Make Sense of Location-Based Micro-posts

  • Irene Celino
  • Daniele Dell’Aglio
  • Emanuele Della Valle
  • Yi Huang
  • Tony Lee
  • Seon-Ho Kim
  • Volker Tresp
Conference paper

DOI: 10.1007/978-3-642-25953-1_7

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7117)
Cite this paper as:
Celino I. et al. (2012) Towards BOTTARI: Using Stream Reasoning to Make Sense of Location-Based Micro-posts. In: García-Castro R., Fensel D., Antoniou G. (eds) The Semantic Web: ESWC 2011 Workshops. ESWC 2011. Lecture Notes in Computer Science, vol 7117. Springer, Berlin, Heidelberg

Abstract

Consider an urban environment and its semi-public realms (e.g., shops, bars, visitors attractions, means of transportation). Who is the maven of a district? How fast and how broad can such maven influence the opinions of others? These are just few of the questions BOTTARI (our Location-based Social Media Analysis mobile app) is getting ready to answer. In this position paper, we recap our investigation on deductive and inductive stream reasoning for social media analysis, and we show how the results of this research form the underpinning of BOTTARI.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Irene Celino
    • 1
  • Daniele Dell’Aglio
    • 1
  • Emanuele Della Valle
    • 2
    • 1
  • Yi Huang
    • 3
  • Tony Lee
    • 4
  • Seon-Ho Kim
    • 4
  • Volker Tresp
    • 3
  1. 1.CEFRIEL – ICT InstitutePolitecnico of MilanoMilanoItaly
  2. 2.Dip. di Elettronica e dell’InformazionePolitecnico di MilanoMilanoItaly
  3. 3.Corporate TechnologySIEMENS AGMuenchenGermany
  4. 4.SaltluxSeoulKorea

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