LIPED: HMM-based life profiles for adaptive event detection

In this paper, the proposed LIPED (LIfe Profile based Event Detection) employs the concept of life profiles to predict the activeness of event for effective event detection. A group of events with similar activeness patterns shares a life profile, modeled by a hidden Markov model. Considering the burst-anddiverse property of events, LIPED identifies the activeness status of event. As a result, LIPED balances the clustering precision and recall to achieve better F1 scores than other well known approaches evaluated on the official TDT1 corpus. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: Clustering, H.2.8 [Database Applications]: Data mining, G.3 [Probability and Statistics]: Time series analysis. General Terms Algorithms, Experimentation, Performance Keywords Event Detection, Life Profiles, Hidden Markov Models, Clustering.

• Type: Conference
• Year: 2005
• Where: KDD
• Authors: Chien Chin Chen, Meng Chang Chen, Ming-Syan Chen
• Keywords: Data Mining, Event Detection, Hidden Markov Models, KDD 2005, Life Profiles