%0 Journal Article
%T Collaborative filtering algorithm using user background information<br>结合用户背景信息的协同过滤推荐算法
%A WU Yi-fan
%A WANG Hao-ran
%A <br>吴一帆
%A 王浩然
%J 计算机应用
%D 2008
%I 
%X Aiming at the difficulty of data sparsity in personalized recommendation systems, a new collaborative filtering algorithm using user background information was presented. The algorithm took full advantage of user data and domain knowledge in hand, modeled user similarity based on user background information and filled in the user-item rating matrix in advance before the traditional collaborative filtering. The experimental results show that the new algorithm can improve the recommendation accuracy efficiently and will not cause bottleneck on performance.
%K personalized recommendation
%K collaborative filtering
%K user background information
%K similarity modeling<br>个性化推荐
%K 协同过滤
%K 用户背景信息
%K 相似度建模
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=3E2E261CAA9DB479CF23522EA06C05A8&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=708DD6B15D2464E8&sid=82A6F761157FD405&eid=94CBA1FA688E6C6E&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=10