%0 Journal Article
%T Link Prediction Based on Node Similarity<br>基于节点相似性的链接预测
%A DONG Yu-xiao
%A KE Qing
%A WU Bin
%A <br>东昱晓
%A 柯庆
%A 吴斌
%J 计算机科学
%D 2011
%I 
%X Link prediction is an important issue in graph mining. It aimed at estimating the likelihood of the existence of links between nodes by the known network structure information. Currently, most link prediction algorithms based on node similarity consider only the individual characteristics of common neighbor nodes. We designed a new algorithm exploiting the interactions between common neighbors, namely Individual Attraction Index While maintaining low time complexity, this algorithm remarkably improved the accuracy of prediction. I}his paper proved well the best overall performance of this new algorithm by comparing three well-known node similarity algorithms on eight real networks with Individual Attraction Index.
%K Complex network
%K Data mining
%K Link prediction
%K Node similarity
%K Individual attraction index<br>复杂网络，数据挖掘，链接预测，节点相似度，节点引力指数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=3FDBEA69C21D71CDD3F941CCED6B6A07&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=DF92D298D3FF1E6E&sid=F1177A9DF1349B63&eid=F260CE035846B3B8&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=17