融合多系统用户信息的协同过滤算法  

Collaborative Filtering Algorithm Fusing Multi-system User Information

作　　者：张付志[1] 张启凤[1] 

机构地区：[1]燕山大学信息科学与工程学院,秦皇岛066004

出　　处：《计算机工程》2009年第21期258-260,263,共4页Computer Engineering

基　　金：河北省自然科学基金资助项目(F2008000877)

摘　　要：为了提高新用户服务的预测准确率,提出一种融合多系统用户信息的协同过滤算法。该算法通过将多个系统的用户信息融合到低维流形中为用户寻找邻居和推荐项目,并介绍流形学习算法在推荐服务中的应用过程。通过对比实验,结果表明该算法比传统协同过滤算法能更有效、准确地为新用户提供推荐。In order to improve the accuracy of forecast for new-user service, this paper proposes a collaborative filtering algorithm fusing multi-system user information. The algorithm finds neighbor and recommendation item by fusing multi-system user information to low dimensional manifold. It introduces the application process of manifold learning algorithm in recommendation service. Result shows that the proved algorithm can be more effective and accurate than traditional collaborative 51tering algorithms for new user by contrastive experiment.

关 键 词：局部不变投影 协同过滤 新用户 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]