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New Trending Events Detection based on the Multi-Representation Index Tree Clustering
International Journal of Intelligent Systems and Applications
Traditional Clustering is a powerful technique for revealing the hot topics among Web information. However, it failed to discover the trending events coming out gradually. In this paper, we propose a novel method to address this problem which is modeled as detecting the new cluster from time-streaming documents. Our approach concludes three parts: the cluster definition based on Multi-Representation Index Tree (MI-Tree), the new cluster detecting process and the metrics for measuring a newdoi:10.5815/ijisa.2011.03.04 fatcat:rxoh2xkizfayjolfzlq3shh65m