• DocumentCode
    262436
  • Title

    Efficient Event Detection for the Blogosphere

  • Author

    Hennig, Patrick ; Berger, Philipp ; Kurzynski, Daniel ; Rantzsch, Hannes ; Meinel, Christoph

  • Author_Institution
    Hasso-Plattner-Inst., Univ. of Potsdam, Potsdam, Germany
  • fYear
    2014
  • fDate
    3-5 Dec. 2014
  • Firstpage
    408
  • Lastpage
    415
  • Abstract
    In this paper we come up with a novel approach for the early detection of events in blog entries. The detection of trend is already discussed pretty often. Nevertheless, in our understanding the detection of events goes one step further. The presented algorithms detects unique happenings at a given point in time by perceiving unusual frequent occurrences of words or word groups. We introduce an implementation of our algorithm, making use of the SAP HANA database in order to achieve high performance and the ability to answer live queries for events.
  • Keywords
    Web sites; SAP HANA database; blogosphere; efficient event detection; live queries; Blogs; Clustering algorithms; Data mining; Databases; Educational institutions; Event detection; Measurement; Blogs; Data Mining; Event Detection; Social Media;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/BDCloud.2014.67
  • Filename
    7034823