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A Study on Retrospective and On-Line Event Detection (1998) [79 citations — 8 self]

by Yiming Yang ,  Tom Pierce ,  Jaime Carbonell
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Abstract:

This paper investigates the use and extension of text retrieval and clustering techniques for event detection. The task is to automatically detect novel events from a temporally-ordered stream of news stories, either retrospectively or as the stories arrive. We applied hierarchical and non-hierarchical document clustering algorithms to a corpus of 15,836 stories, focusing on the exploitation of both content and temporal information. We found the resulting cluster hierarchies highly informative for retrospective detection of previously unidentified events, effectively supporting both query-free and query-driven retrieval. We also found that temporal distribution patterns of document clusters provide useful information for improvement in both retrospective detection and on-line detection of novel events. In an evaluation using manually labelled events to judge the system-detected events, we obtained a result of 82% in the F1 measure for retrospective detection, and a F1 value of 42% for...

Citations

988 Automatic Text Processing -- The Transformation, Analysis, and Retrieval of Information by Computer Addison-Wesley – Salton - 1989
430 Scatter/gather: a cluster-based approach to browsing large document collections – Cutting, Karger, et al. - 1992
169 Recent trends in hierarchic document clustering: a critical review – Willett - 1988
124 Optimal algorithms for approximate clustering – Feder, Greene - 1988
44 Document filtering with inference networks – Callan - 1996
15 Automated query-relevant summarization and diversity-based reranking – Carbonell, Geng, et al. - 1997
3 Support for browsing in an intelligent text retrieval system – Tohompson, Croft - 1989
2 Implementing allgomerative hierarchic clustering algorithms for use in document retrieval – Voorhees - 1986
1 Topic detection and tracking: Detection-task – Yang, Carbonell, et al. - 1997