Study on Key Technology for Topic Tracking

摘要

Text classification is the key technology for topic tracking, and vector space model (VSM) is one of the most simple and effective model for topics representation. On the basis of Knearest neighbor (KNN) algorithm for text classification and support vector machines (SVM) algorithm for text classification, we have studied how they affect topic tracking. Then we get the variation law that they affect topic tracking, and add up their optimal values in topic tracking. Finally, TDT evaluation method proves that optimal topic tracking performance based on SVM increases by 35.134% more than KNN.