IDEAS home Printed from https://ideas.repec.org/a/bla/jamist/v54y2003i7p621-624.html
   My bibliography  Save this article

Introduction to the JASIST Special Topic issue on web retrieval and mining: A machine learning perspective

Author

Listed:
  • Hsinchun Chen

Abstract

No abstract is available for this item.

Suggested Citation

  • Hsinchun Chen, 2003. "Introduction to the JASIST Special Topic issue on web retrieval and mining: A machine learning perspective," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(7), pages 621-624, May.
    • Handle: RePEc:bla:jamist:v:54:y:2003:i:7:p:621-624
    DOI: 10.1002/asi.10254
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asi.10254
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asi.10254?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
    ---><---

    Citations

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


    Cited by:

    1. Şenay Yaşar Sağlam & W. Nick Street, 2018. "Distant diversity in dynamic class prediction," Annals of Operations Research, Springer, vol. 263(1), pages 5-19, April.
    2. Kazim Topuz & Hasmet Uner & Asil Oztekin & Mehmet Bayram Yildirim, 2018. "Predicting pediatric clinic no-shows: a decision analytic framework using elastic net and Bayesian belief network," Annals of Operations Research, Springer, vol. 263(1), pages 479-499, April.
    3. Alaleh Razmjoo & Petros Xanthopoulos & Qipeng Phil Zheng, 2019. "Feature importance ranking for classification in mixed online environments," Annals of Operations Research, Springer, vol. 276(1), pages 315-330, May.
    4. Sylvie Tchumtchoua & Dipak Dey, 2012. "Modeling Associations Among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 670-692, October.

    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:bla:jamist:v:54:y:2003:i:7:p:621-624. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    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.