WWW2006 - Discovering Event Evolution Graphs from Newswires
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Discovering Event Evolution Graphs from Newswires

  • Christopher C. Yang, The Chinese University of Hong Kong, Hong Kong
  • Xiaodong Shi, The Chinese University of Hong Kong, HK

Track: Posters

In this paper, we propose an approach to automatically mine event evolution graphs from newswires on the Web. Event evolution graph is a directed graph in which the vertices and edges denote news events and the evolutions between events respectively, in a same news affair. Our model utilizes the content similarity between events and incorporates temporal proximity and document distributional proximity as decaying functions. Our approach is effective in presenting the inside developments of news affairs along the timeline, which can facilitate users' information browsing tasks.

Other items being presented by these speakers

  • Mining Related Queries from Search Engine Query Logs (Posters Track)
  • Discovering Event Evolution Graphs from Newsires (Posters Track)

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