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With the advancement in internet technology, users can now easily extract large number of news stories of any ongoing incidents from existing newswires. These hundreds and thousands of news stories causes the problem of information overload. Users find difficulty in capturing the blueprint of the incident as the volume of information is too large. So it becomes necessary to organize news stories into events and learn how these events developed or evolved within the topic. This paper discusses some of the efforts made to model and discover relationships between news events, which had been a less focused area as compared to TDT research which solely focused flat hierarchical structure. A real-world example is discussed for event evolution analysis and future extensions have been proposed. General Terms News events, News stories, Component events, Web search engines.

Event Evolution Modeling for Efficient News Search