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协同过滤推荐系统中数据稀疏问题的解决 被引量：51

Algorithm for Sparse Problem in Collaborative Filtering
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摘要 介绍了现有协同过滤推荐的几种主要算法。它们对数据稀疏性问题都有一定的缓和作用。通过在数据集MovieLens上的实验,分析了各个算法在不同稀疏度下的推荐质量,为针对不同数据稀疏度的系统实现提供了可靠依据。 This paper summarized several primary algorithms, and experimented on MovieLens data. And analyzed different algorithm with the experimental results.
作者 吴颜 沈洁 顾天竺 陈晓红 李慧 张舒
机构地区 扬州大学信息工程学院计算机科学系
出处 《计算机应用研究》 CSCD 北大核心 2007年第6期94-97,共4页 Application Research of Computers
基金 江苏省自然科学基金资助项目(BK2005046)
关键词 电子商务 推荐系统 协同过滤 数据稀疏 相似性 e-commerce recommender system collaborative filtering data sparse similarity
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献17

  • 1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：554
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二级参考文献13

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计算机应用研究
2007年 第6期

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