• DocumentCode
    2276495
  • Title

    A Survey: Approaches for Handling Evolving Data Streams

  • Author

    Wankhade, K. ; Hasan, T. ; Thool, R.

  • Author_Institution
    Dept. of Inf. Technol., G.H. Raisoni Coll. of Eng., Nagpur, India
  • fYear
    2013
  • fDate
    6-8 April 2013
  • Firstpage
    621
  • Lastpage
    625
  • Abstract
    The increasing use of technology in diverse field has caused generation of huge volumes of information streams. Data streams contains bulk of data points generated at high speed continuously from various applications like log records, web clicks etc. With recent advancement in technology need for analysis of such unbounded streams is increasing day by day. Data mining process helps to excavate useful knowledge from rapidly generated raw data streams. In context with the continuously generated data, mining data streams is emerging challenging task in which several issues like limited space, limited time, accuracy, handling evolving data need to be considered. This paper provides an overview of various approaches for handling changing and evolving data streams.
  • Keywords
    data handling; data mining; Web clicks; data handling; data mining process; data streams; information streams; limited space; limited time; log records; Accuracy; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Conferences; Context; Data mining; Data streams; classification; clustering; concept drift; data mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems and Network Technologies (CSNT), 2013 International Conference on
  • Conference_Location
    Gwalior
  • Print_ISBN
    978-1-4673-5603-9
  • Type

    conf

  • DOI
    10.1109/CSNT.2013.133
  • Filename
    6524476