IDEAS home Printed from https://ideas.repec.org/a/igg/jdwm00/v10y2014i2p39-54.html
   My bibliography  Save this article

HASTA: A Hierarchical-Grid Clustering Algorithm with Data Field

Author

Listed:
  • Shuliang Wang

    (School of Software, Beijing Institute of Technology, Haidian, Beijing, China)

  • Yasen Chen

    (Tencent Inc., Nanshan, Shenzhen, China)

Abstract

In this paper, a novel clustering algorithm, HASTA (HierArchical-grid cluStering based on daTA field), is proposed to model the dataset as a data field by assigning all the data objects into qusantized grids. Clustering centers of HASTA are defined to locate where the maximum value of local potential is. Edges of cluster in HASTA are identified by analyzing the first-order partial derivative of potential value, thus the full size of arbitrary shaped clusters can be detected. The experimented case demonstrates that HASTA performs effectively upon different datasets and can find out clusters of arbitrary shapes in noisy circumstance. Besides those, HASTA does not force users to preset the exact amount of clusters inside dataset. Furthermore, HASTA is insensitive to the order of data input. The time complexity of HASTA achieves O(n). Those advantages will potentially benefit the mining of big data.

Suggested Citation

  • Shuliang Wang & Yasen Chen, 2014. "HASTA: A Hierarchical-Grid Clustering Algorithm with Data Field," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 10(2), pages 39-54, April.
    • Handle: RePEc:igg:jdwm00:v:10:y:2014:i:2:p:39-54
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijdwm.2014040103
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jdwm00:v:10:y:2014:i:2:p:39-54. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.