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协同过滤算法中一种改进的预测值计算方法 被引量：2

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摘要 传统的协同过滤算法中预测值的计算只考虑了用户评分而缺乏对用户评分是否可信的考虑,针对这个问题,文章提出了对用户的评分进行信用评估的方法。实验表明,改进后的协同过滤算法在推荐效果方面得到了更好的改善。
作者 陈春明 徐义峰
机构地区 桂林电子科技大学图书馆 衢州学院信息与电子工程系
出处 《情报探索》 2009年第8期79-82,共4页 Information Research
关键词 个性化服务 协同过滤 可信度 预测值
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献7

  • 1Greg Linden,Brent Smith,Jeremy York. Amazon. Com Recommendations:item-to-item collaborative filtering. IEEE Internet Computing, 2003,7 ( 1 ).
  • 2邓爱林,朱扬勇,施伯乐.基于项目评分预测的协同过滤推荐算法[J].软件学报,2003,14(9):1621-1628. 被引量：566
  • 3Karypis G.. Evaluation of item-based top-N recommen- dation algorithms. In:Proceedings of CIKM 2001 ,Atlanta,ACM Press, 2001.
  • 4Adomavieius G, ,Tuzhilin A. Toward the next generadon of recommender systems:a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 2005,17 (6).
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二级参考文献13

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2009年 第8期

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