Design of Hot Web Event Detection System
Long Chen · Zhongwen xinxi xuebao · 2008
We propose a system to detect hot web event automatically.The system is focused on the stream of news report on the Internet,which provides a diagram concerning the tendency of the event and can be utilized to detect the hot web event in any period of time.Since news corpus is characterized by large scale data and distinct time features,it is divided into hundreds of groups according to the date.We further divide each group into some macro-clusters using the agglomerative clustering,select the macro-clusters during a certain period of time and then combine all these selected macro-clusters into event lists by the Single-pass clustering.Finally,we sort the candidate events by calculating their hot degree.Experiments on 2007 news corpus show that our system can produce satisfactory results.