%0 Journal Article
%T Clustering User Access Patterns based on Fuzzy Rough k-Means<br>基于模糊粗糙k-均值的用户访问模式的聚类
%A WU Rui
%A NING Yu-fu
%A <br>吴瑞
%A 宁玉富
%J 系统工程理论与实践
%D 2007
%I 
%X The interest of web users can be revealed by their visited web pages and time durations on these web pages during their susfing.In order that similarity/difference between any two patterns can be easily gained,each web access pattern from web logs is transformed as fuzzy vector with same length,in which each element is a fuzzy linguistic variable or 0 representing the visited web page and time duration on this web page.The clusters may not exist crisp boundaries,thus a rough k-means clustering algorithm is proposed to group the fuzzy vectors denoting users' surfing behaviors.Finally,Davies-Bouldin index is provided to measure the clustering exactness.
%K web mining
%K web clustering
%K user access patterns
%K rough k-means<br>Web挖掘
%K Web聚类
%K 用户浏览模式
%K 粗糙k-均值
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=962324E222C1AC1D&jid=1D057D9E7CAD6BEE9FA97306E08E48D3&aid=3BC66BCEFC3F1A76&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=DF92D298D3FF1E6E&sid=8477411EEDB08A86&eid=CDEBD1ACE0A4C1C1&journal_id=1000-6788&journal_name=系统工程理论与实践&referenced_num=0&reference_num=9