1998 TopicDetectionAndTrackingPilotStudy

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Subject Headings: Topic Detection and Tracking, Topic Detection, Topic Tracking.


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Topic Detection and Tracking (TDT) is a DARPA-sponsored initiative to investigate the state of the art in finding and following new events in a stream of broadcast news stories. The TDT problem consists of three major tasks: (1) segmenting a stream of data, especially recognized speech, into distinct stories; (2) identifying those news stories that are the first to discuss a new event occurring in the news; and (3) given a small number of sample news stories about an event, finding all following stories in the stream.

The TDT Pilot Study ran from September 1996 through October 1997. The primary participants were DARPA, Carnegie Mellon University, Dragon Systems, and the University of Massachusetts at Amherst. This report summarizes the findings of the pilot study. The TDT work continues in a new project involving larger training and test corpora, more active participants, and a more broadly defined notion of “topic” than was used in the pilot study.

The following individuals participated in the research reported.

James Allan, UMass
Brian Archibald, CMU
Doug Beeferman, CMU
Adam Berger, CMU
Ralf Brown, CMU
Jaime Carbonell, CMU
Ira Carp, Dragon
Bruce Croft, UMass,
George Doddington, DARPA
Larry Gillick, Dragon
Alex Hauptmann, CMU
John Lafferty, CMU
Victor Lavrenko, UMass
Xin Liu, CMU
Steve Lowe, Dragon
Paul van Mulbregt, Dragon
Ron Papka, UMass
Thomas Pierce, CMU
Jay Ponte, UMass
Mike Scudder, UMass
Charles Wayne, DARPA
Jon Yamron, Dragon
Yiming Yang, CMU,

 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
1998 TopicDetectionAndTrackingPilotStudyJames Allan
Jaime G. Carbonell (1953 – 2020)
George Doddington
Jonathan Yamron
Yiming Yang
Topic Detection and Tracking Pilot Study: Final reportProceedings of the DARPA Broadcast News Transcription and Understanding Workshophttp://www.cs.cmu.edu/~jgc/publication/Topic Detection Tracking Pilot DARPA 1998.pdf1998