• DocumentCode
    3652539
  • Title

    Automatic Analysis of Large Data Sets: A Walk-Through on Methods from Different Perspectives

  • Author

    Marcus Hilbrich;Matthias Weber;Ronny Tschüter

  • Author_Institution
    Center for Inf. Services &
  • fYear
    2013
  • Firstpage
    373
  • Lastpage
    380
  • Abstract
    Analyzing data is one of today´s hot topics. A complete list of fields of research and buzzwords associated with automatic analysis would extend beyond this document. The importance of this topic stems from the amount of data currently produced in research, engineering, and other fields. The size of these data sets renders manual analysis infeasible. Automatic analysis methods are required to cope with the data sets produced. The algorithms for filtering, categorization, and analysis have a long tradition and are manifold. This raises the question for the best algorithm. The authors of this paper give an overview about manifold automatic analysis approaches along with a classification of these approaches with regard to three different fields of research.
  • Keywords
    "Bioinformatics","Genomics","Clustering algorithms","Sociology","Statistics","Heuristic algorithms","Monitoring"
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on
  • Type

    conf

  • DOI
    10.1109/CLOUDCOM-ASIA.2013.47
  • Filename
    6821018