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Topic Detection and Tracking for News Web Pages
Hong Kong, China December 18-December 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WI.2006.1712006 IEEE/WIC/ACM International Confe ...
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Masaki Mori, Hosei University, Japan
Takao Miura, Hosei University, Japan
Isamu Shioya, Sanno University, Japan
This paper propose a new approach to observe, summarize and track events from a collection of news Web Pages. Given a set of temporal Web pages, we obtain valid timestamp from Web pages and detect events by means of clustering. Then we track events by using KeyGraph based on the clusters and abstract the clusters by using SuffixTree. We examine some experimental results and show the usefulness of our approach.
Index Terms:
Web Mining, TDT, Web Abstraction
Citation:
Masaki Mori, Takao Miura, Isamu Shioya, "Topic Detection and Tracking for News Web Pages," wi, pp.338-342, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI'06), 2006
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