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In this paper, an adaptive news event detection method is proposed. We consider a news event as a life form and propose an aging theory to model its life span. A news event becomes popular with a burst of news reports, and it fades away with time. We incorporate the proposed aging theory into the tradi- tional single-pass clustering algorithm to model life spans of news events. Ex- periment results show that the proposed method has fairly good performance for both long-running and short-term events compared to other approaches.

Life Cycle Modeling of News Events Using Aging Theory