IDEAS home Printed from https://ideas.repec.org/a/bla/jamist/v61y2010i4p802-819.html
   My bibliography  Save this article

New event detection and topic tracking in Turkish

Author

Listed:
  • Fazli Can
  • Seyit Kocberber
  • Ozgur Baglioglu
  • Suleyman Kardas
  • H. Cagdas Ocalan
  • Erkan Uyar

Abstract

Topic detection and tracking (TDT) applications aim to organize the temporally ordered stories of a news stream according to the events. Two major problems in TDT are new event detection (NED) and topic tracking (TT). These problems focus on finding the first stories of new events and identifying all subsequent stories on a certain topic defined by a small number of sample stories. In this work, we introduce the first large‐scale TDT test collection for Turkish, and investigate the NED and TT problems in this language. We present our test‐collection‐construction approach, which is inspired by the TDT research initiative. We show that in TDT for Turkish with some similarity measures, a simple word truncation stemming method can compete with a lemmatizer‐based stemming approach. Our findings show that contrary to our earlier observations on Turkish information retrieval, in NED word stopping has an impact on effectiveness. We demonstrate that the confidence scores of two different similarity measures can be combined in a straightforward manner for higher effectiveness. The influence of several similarity measures on effectiveness also is investigated. We show that it is possible to deploy TT applications in Turkish that can be used in operational settings.

Suggested Citation

  • Fazli Can & Seyit Kocberber & Ozgur Baglioglu & Suleyman Kardas & H. Cagdas Ocalan & Erkan Uyar, 2010. "New event detection and topic tracking in Turkish," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(4), pages 802-819, April.
    • Handle: RePEc:bla:jamist:v:61:y:2010:i:4:p:802-819
    DOI: 10.1002/asi.21264
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asi.21264
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asi.21264?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. Cagri Toraman & Fazli Can, 2017. "Discovering story chains: A framework based on zigzagged search and news actors," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2795-2808, December.

    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:61:y:2010:i:4:p:802-819. 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.