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In this paper, high performance real-time detecting and tracking technology for news events are proposed. The difference to previous TDT articles in the detection and tracking is that this attempt to establish the historical hotspot events Corpus first, and analyze the characteristics of the corpus according to timeline. HMM-based named entity recognition model is also used to find out other event characteristics except those reference timeline. By combining the above two methods and SVM, this study proposes its models in detecting and tracking. Experiments presented in this paper shows the models having a high performance in recall and precision.