IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-662-43871-8_235.html
   My bibliography  Save this book chapter

Adaptive Real-Time Clustering Algorithm with Resource-Aware

In: Liss 2014

Author

Listed:
  • Xiaoni Wang

    (Beijing Information Science and Technology University)

Abstract

In order to effectively consider the problems of limited resources of equipment node’s memory capacity, processing power, and battery power in the environment of data stream, the method of fast and effective extraction mining knowledge is analyzed. DRA-Kmeans clustering algorithm is proposed on the basis of CluStream algorithm, which combines with RA-Cluster algorithm and introduces the adaptive clustering method and improves CluStream algorithm. The clustering accuracy is increased and clustering effective range is optimized in the case of resource constraints.

Suggested Citation

  • Xiaoni Wang, 2015. "Adaptive Real-Time Clustering Algorithm with Resource-Aware," Springer Books, in: Zhenji Zhang & Zuojun Max Shen & Juliang Zhang & Runtong Zhang (ed.), Liss 2014, edition 127, pages 1635-1639, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-43871-8_235
    DOI: 10.1007/978-3-662-43871-8_235
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-662-43871-8_235. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.