An Improved Agglomerative Levels K-Means Clustering Algorithm

Abstract

The paper proposed a method which combines an improved hierarchical aggregation and K-means clustering algorithm, overcoming the selection problem of initial cluster centers and selection problem of termination condition. Application this method to cluster sina weibo topic and compare with tradition hierarchical aggregation and K-means clustering algorithm, finding the method can reduce false positives and missed rate.