• DocumentCode
    3689363
  • Title

    Exploratory analysis of large web datasets

  • Author

    Silvana Castano;Alfio Ferrara;Stefano Montanelli

  • Author_Institution
    Department of Computer Science, Università
  • fYear
    2015
  • Firstpage
    243
  • Lastpage
    248
  • Abstract
    In the era of big data, the capability to identify very quickly prominent summary information about a target entity of interest, like a person or an event, from large datasets is essential, and exploratory analysis techniques help in this direction. In this paper, we provide a solution based on smart entity views and on pre-defined analysis operators which exploit keywords available in the entity view together with similarity information to produce summary information about the view contents from both a thematic and analytics perspective. In particular, smart entity views can be analyzed according to the following exploratory paradigms: entity expansion, entity visualization, and entity analytics. The proposed approach is discussed by referring to a case study of twitter dataset related to the “Expo2015” event as target entity.
  • Keywords
    "Correlation","Information services","Chlorine","Clustering algorithms","Twitter","Visualization","Tagging"
  • Publisher
    ieee
  • Conference_Titel
    Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI), 2015 IEEE 1st International Forum on
  • Type

    conf

  • DOI
    10.1109/RTSI.2015.7325105
  • Filename
    7325105