Dynamic stopwording for story link detection

Authors:
Ralf D. Brown
Affiliations:
Carnegie Mellon University, Pittsburgh, PA
Venue:
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Year:
2002

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Abstract

Carnegie Mellon University entered two systems in the Story Link Detection track of the 2001 Topic Detection and Tracking (TDT) evaluation. These systems were one of our systems from the 1999 TDT evaluation [1], retuned for the new corpus, which had the third-best cost measure; and a new system that adds clustering and dynamically-generated stopwording, which had the best cost measure among all submissions for the default evaluation condition. This paper describes the enhancements which were made and some which were attempted but not used in the evaluation.