• DocumentCode
    1416415
  • Title

    Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics

  • Author

    Barbieri, Davide ; Braga, Daniele ; Ceri, Stefano ; Valle, E.D. ; Huang, Yi ; Tresp, Volker ; Rettinger, Achim ; Wermser, Hendrik

  • Volume
    25
  • Issue
    6
  • fYear
    2010
  • Firstpage
    32
  • Lastpage
    41
  • Abstract
    A combined approach of deductive and inductive reasoning can leverage the clear separation between the evolving (streaming) and static parts of online knowledge at conceptual and technological levels. What are the hottest topics discussed on Twitter? Which topics have my close friends discussed in the last hour? Which movie is my friend most likely to watch next? Which Tuscan red wine should I recommend? With many popular social networks publishing microblogs and feeds, the information required to answer these queries is becoming available on the Web.
  • Keywords
    Internet; social networking (online); Twitter; deductive stream reasoning; inductive stream reasoning; online knowledge; semantic social media analytics; social networks; Cognition; Data mining; Engines; Media; Motion pictures; Real time systems; Resource description framework; C-SPARQL; RDF streams; SPARQL; deductive reasoning; inductive reasoning; online learning; social media analytics; stream reasoning;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2010.142
  • Filename
    5678584