Title :
On-line new event detection using time window strategy
Author :
Xu, Rui-Feng ; Peng, Wei-Hua ; Xu, Jun ; Long, Xiao
Author_Institution :
Shenzhen Grad. Sch., Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Shenzhen, China
Abstract :
New Event Detection is the task of automatically detecting novel events from a temporally-ordered stream of news story documents. Traditionally, on-line new event detection system determines whether the incoming document contains a new event based on the history of all processed documents. With the improvement of processed documents, the efficiency of on-line new event detection will decrease. In this paper, we apply a time window strategy to new event detection. A group of new incoming documents in the time window are firstly clustered to obtain candidate topics. Next, these candidate topics are compared with the previously identified topics to determine whether a new topic is detected. The first story of the new detected topic, in temporal order, is regarded as a new event. By analyzing the news story documents within the time window in group, the new event detection efficiency is improved. Furthermore, the evaluations show that the time window processing strategy is helpful to improve the accuracy of new event detection.
Keywords :
Internet; document handling; pattern clustering; news story document processing; on-line new event detection; temporally-ordered stream; time window strategy; Clustering algorithms; Cybernetics; Event detection; Machine learning; Real time systems; Time frequency analysis; Vocabulary; Clustering; New Event Detection; Time Window;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4577-0305-8
DOI :
10.1109/ICMLC.2011.6016957