Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Topic Detection and Tracking

  • Ning Liu
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_430

Definition

According to the definition at http://projects.ldc.upenn.edu/TDT/, Topic Detection and Tracking (TDT) is a multi-site research project to develop core technologies for a news understanding systems. Specifically, TDT systems discover the topical structure in unsegmented streams of news reporting as it appears across multiple media and in different languages. Some terms are defined below before the TDT problem is fully understood (The definitions are borrowed from Omid Dadgar’s work).
  1. 1.

    Event – An event is something that happens at some specific time and place, and the unavoidable consequences. Specific elections, accidents, crimes and natural disasters are examples of events.

     
  2. 2.

    Activity – An activity is a connected set of actions that have a common focus or purpose. Specific campaigns, investigations, and disaster relief efforts are examples of activities.

     
  3. 3.

    Story – A story is a newswire article or a segment of a news broadcast with a coherent news focus. They must...

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Recommended Reading

  1. 1.
    Allan J. Topic detection and tracking. Norvell: Kluwer; 2002.zbMATHCrossRefGoogle Scholar
  2. 2.
    Allan J, Carbonell J, Doddington G, Yamron J, Yang Y. Topic detection and tracking pilot study final report. In: Proceedings of the DARPA Broadcast News Transcription and Understanding Workshop; 1998. p. 194–218.Google Scholar
  3. 3.
    Makkonen J, Ahonen-Myka H. Utilizing temporal expressions in topic detection and tracking. In: Proceedings of the 7th European Conference Research and Advanced Technology for Digital Libraries; 2003. p. 393–404.zbMATHCrossRefGoogle Scholar
  4. 4.
    Mori M, Miura T, Shioya I. Topic detection and tracking for news web pages. In: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence; 2006. p. 338–42.Google Scholar
  5. 5.
    Ruifang H, Bing Q, Ting L, Sheng L. The topic detection and tracking with topic sensitive language model. In: Proceedings of the International Conference on Mutilingual Information Processing; 2005. p. 324–7.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Microsoft Research AsiaBeijingChina

Section editors and affiliations

  • Zheng Chen
    • 1
  1. 1.Microsoft Research AsiaMicrosoft CorporationBeijingChina