Profile-based event tracking

Authors:
Baoli Li;Wenjie Li;Qin Lu;Mingli Wu
Affiliations:
The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Venue:
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2005

Citing 2
Cited 4

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Abstract

In this research, we focus on tracking topics that originate and evolve from a specific event. Intuitively, a few key elements of a target event, such as date, location, and persons involved, would be enough for making a decision on whether a test story is on-topic. Consequently, a profile-based event tracking method is proposed. We attempt to build an event profile from the given on-topic stories by robust information retrieval technologies. A feature selection metric and a recognized event clause are utilized to determine most (if not all) key semantic elements of the target event. Preliminary experiments on the TDT2 mandarin corpus show that this profile-based event tracking method is promising.