IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v07y2008i02ns0219622008002971.html
   My bibliography  Save this article

Web Farming With Clickstream

Author

Listed:
  • JIA HU

    (International WIC Institute, Beijing University of Technology, No. 100 Ping Le Yuan, Chao Yang District, Beijing 100022, China)

  • NING ZHONG

    (Department of Life Science and Informatics, Maebashi Institute of Technology, 460-1 Kamisadori, Maebashi, Gunma 371-0816, Japan)

Abstract

In a commercial website or portal, Web information fusion is usually from the following two approaches, one is to integrate the Web content, structure, and usage data for surfing behavior analysis; the other is to integrate Web usage data with traditional customer, product, and transaction data for purchasing behavior analysis. In this paper, we propose a unified model based on Web farming technology for collecting clickstream logs in the whole user interaction process. We emphasize that collecting clickstream logs at the application layer will help to seamlessly integrate Web usage data with other customer-related data sources.In this paper, we extend the Web log standard to modeling clickstream format and Web mining to Web farming from passively collecting data and analyzing the customer behavior to actively influence the customer's decision making. The proposed model can be developed as a common plugin for most existing commercial websites and portals.

Suggested Citation

  • Jia Hu & Ning Zhong, 2008. "Web Farming With Clickstream," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 291-308.
    • Handle: RePEc:wsi:ijitdm:v:07:y:2008:i:02:n:s0219622008002971
    DOI: 10.1142/S0219622008002971
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622008002971
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219622008002971?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. M. Ballings & D. Van Den Poel & E. Verhagen, 2013. "Evaluating the Added Value of Pictorial Data for Customer Churn Prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/869, Ghent University, Faculty of Economics and Business Administration.
    2. Philippe Baecke & Dirk Van Den Poel, 2010. "Improving Purchasing Behavior Predictions By Data Augmentation With Situational Variables," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 9(06), pages 853-872.
    3. Gang Kou & Chunwei Lou, 2012. "Multiple factor hierarchical clustering algorithm for large scale web page and search engine clickstream data," Annals of Operations Research, Springer, vol. 197(1), pages 123-134, August.
    4. M. Ballings & D. Van Den Poel, 2012. "The Relevant Length of Customer Event History for Churn Prediction: How long is long enough?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/804, Ghent University, Faculty of Economics and Business Administration.

    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:ijitdm:v:07:y:2008:i:02:n:s0219622008002971. 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.worldscinet.com/ijitdm/ijitdm.shtml .

    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.