• DocumentCode
    3717163
  • Title

    Big data entity resolution: From highly to somehow similar entity descriptions in the Web

  • Author

    Vasilis Efthymiou;Kostas Stefanidis;Vassilis Christophides

  • Author_Institution
    University of Crete, Greece
  • fYear
    2015
  • Firstpage
    401
  • Lastpage
    410
  • Abstract
    In the Web of data, entities are described by interlinked data rather than documents on the Web. In this work, we focus on entity resolution in the Web of data, i.e., identifying descriptions that refer to the same real-world entity. To reduce the required number of pairwise comparisons, methods for entity resolution perform blocking as a pre-processing step. A blocking technique places similar entity descriptions into blocks and executes comparisons only between descriptions within the same block. We experimentally evaluate blocking techniques proposed for the Web of data and present dataset characteristics that determine the effectiveness and efficiency of such methods. Furthermore, we analyze the characteristics of the missed matching entity descriptions and examine different types of links that blocking techniques can potentially identify.
  • Keywords
    "Erbium","Big data","Semantics","Poles and towers","Context","Clustering algorithms","Conferences"
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/BigData.2015.7363781
  • Filename
    7363781