Hot Topic Clustering Based On Words Distances

Abstract

Abstract. In order to find the relevance of the key words in the hot topics effectively, we proposed a clustering method based on words-distances. We calculated the distances between the words firstly, then calculated the sectional density of each words. We regarded the words which have higher sectional density and far away from sectional density point as the center point in the clustering. After find the center point, we start to clustering. This method through decision diagram on estimating the number of clusters. At last, we can find the results on the evaluating indicator of accuracy rate and recall rate.