Abstract
We discuss Topic Detection, a sub-task of the Topic Detection and Tracking (TDT) Project, and present a system that uses the linguistic and temporal features of news reportage to enhance the discovery of events in a collection of news articles. We describe an online application of these techniques that constructs topical clusters from live news feeds. We conclude that these approaches promise more coherent and useful clusters and suggest some areas of future work.
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Flynn, C., Dunnion, J. (2004). Domain-Informed Topic Detection. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2004. Lecture Notes in Computer Science, vol 2945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24630-5_76
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DOI: https://doi.org/10.1007/978-3-540-24630-5_76
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21006-1
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