Proposes a method to discover hot-word relations based on topic clustering.For word discovering,vector space mode is built by extracting document features from news text,and the hot-spot cluster is achieved by K-means algorithm with ameliorated initial center.Up to the hot-word association,hot words relations are analyzed according to the weighted sum of three factors,which include the word category distance computed by the hot-spot cluster,the news co-occurrence rate and the hot words co-occurrence rate.This approach has been successfully applied to Public Opinion Monitoring System of Univers...
