Abstract
Topic detection and tracking approaches monitor broadcast news in order to spot new, previously unreported events and to track the development of the previously spotted ones. The dynamical nature of the events makes the use of state-of-the-art methods difficult. We present a new topic definition that has potential to model evolving events. We also discuss incorporating ontologies into the similarity measures of the topics, and illustrate a dynamic hierarchy that decreases the exhaustive computation performed in the TDT process. This is mainly work-in-progress.
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CITATION STYLE
Makkonen, J. (2003). Investigations on event evolution in TDT. In Proceedings of the 2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics - Student Research Workshop, HLT-NAACL 2003 (pp. 43–48). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1073416.1073424
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