Web document clustering based on web-log mining
Zhao Xiao-bi · Jisuanji gongcheng yu sheji · 2008
Web log mining is one of the web mining.The process of the web log mining and the k-means algorithms are introduced.And the shortage of the k-means algorithm is analyzed.The k-means algorithm needs to compute the distance between every data object and the center of the clusters,which lowers the efficiency.To this problem,an enhanced algorithm of the k-means is put forward,which avoids computing the distance between every data object and the center of the clusters.Web document clustering is implemented with two algorithms and it is shown that the enhanced algorithm improves the clustering efficiency.