Discovering Event Evolution Graphs from Newswires

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

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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.

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