%0 Journal Article
%T Mining Web community based on improved maximum flow algorithm<br>一种改进的基于最大流的Web社区挖掘算法
%A ZHANG Jin-zeng
%A FAN Ming
%A <br>张金增
%A 范明
%J 计算机应用
%D 2009
%I 
%X Given that the original maximum flow algorithm set a fixed edge capacity to each edge, which caused poor quality and improper size of communities, this paper proposed an improved algorithm for mining Web communities. The algorithm considered the differences between edges in terms of importance, and assigned different capacities to different edges by transforming the significant measurements of pages evaluated by weighted PageRank algorithm to edge-transferring probability scores to measure the importance of edges, and assigning them to corresponding edges as their capacities. The experimental results show that the improved maximum flow algorithm improves the quality of Web community effectively.
%K web community
%K web graph
%K maximum flow algorithm
%K weighted PageRank<br>Web社区
%K Web图
%K 最大流算法
%K 加权PageRank
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=D9D4F52811928F8EE32F25E93E30A387&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=CA4FD0336C81A37A&sid=527AEE9F3446633A&eid=CEC789B3C68C3BB3&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=9