IDEAS home Printed from https://ideas.repec.org/h/wsi/wschap/9789812701527_0019.html
   My bibliography  Save this book chapter

Predicting Rare Events In Time Series

In: Knowledge Management Nurturing Culture, Innovation, and Technology

Author

Listed:
  • JUNJIE HOU

    (School of Software, Tsinghua University, 100084, Beijing, China)

  • CHUNPING LI

    (Data Mining Group, Institute of Information System & Engineering, School of Software, Tsinghua University, 100084, Beijing, China)

Abstract

Event prediction is one of the main purposes in association rule mining. In this paper, we propose an approach for predicting rare events efficiently, like engine failures, stock price situations and market analysis etc. We associate a transaction as ordinal event series that occur in equal length intervals and formulate the problem of predicting rare events. Furthermore, an algorithm for discovering valuable patterns in time series is given.

Suggested Citation

  • Junjie Hou & Chunping Li, 2005. "Predicting Rare Events In Time Series," World Scientific Book Chapters, in: Suliman Hawamdeh (ed.), Knowledge Management Nurturing Culture, Innovation, and Technology, chapter 19, pages 221-229, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812701527_0019
    as

    Download full text from publisher

    File URL: https://www.worldscientific.com/doi/pdf/10.1142/9789812701527_0019
    Download Restriction: Ebook Access is available upon purchase.
    File URL: https://www.worldscientific.com/doi/abs/10.1142/9789812701527_0019
    Download Restriction: Ebook Access is available upon purchase.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:wsi:wschap:9789812701527_0019. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscientific.com/page/worldscibooks .

    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.