%0 Journal Article
%T A Web Personalized Recommendation Method Based on Uncertain Consequent Association Rules<br>一种基于后项不定长关联规则的Web个性化推荐方法
%A DING Zeng-Xi WANG Ju-Ying WANG Da-Ling BAO Yu-Bin YU Ge
%A <br>丁增喜
%A 王菊英
%A 王大玲
%A 鲍玉斌
%A 于戈
%J 计算机科学
%D 2003
%I 
%X Web usage mining plays an important part in supporting personalized recommendation on Web and association rule uncovers the interesting relations among items hidden in data. The paper gives an idea of association rule merging-deleting based on the analysis of association rule characteristics and implements it in the rule preparation before the Web personalized recommendation. Furthermore, based on the comparisons in precision, coverage and F1 of recommendation system and the rule numbers used in three kinds of association rules, a Web personalized recommendation method based on uncertain consequent is put forward. After integrative analysis of several recommendation methods, the method given in the paper can be thought as a good selection. At last several page-weighted techniques are introduced in the paper.
%K Association rule
%K Web usage mining
%K Personalized recommendation
%K Precision
%K Coverage<br>Internet
%K Web
%K 个性化推荐方法
%K 后项不定长关联规则
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=D4A8F6C408FA247A&yid=D43C4A19B2EE3C0A&vid=340AC2BF8E7AB4FD&iid=59906B3B2830C2C5&sid=CB423C9A71560A74&eid=AA76E167F386B6B3&journal_id=1002-137X&journal_name=计算机科学&referenced_num=1&reference_num=16