| 基于组合加权评分的Item-based协同过滤算法 |
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| 引用本文： | 马丽.基于组合加权评分的Item-based协同过滤算法[J].现代图书情报技术,2008,24(11):60-64. |
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| 作者姓名： | 马丽 |
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| 作者单位： | 西华师范大学商学院,南充,637002 |
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| 摘 要： | 针对Item-based协同过滤算法中用户评分数据稀疏性严重影响推荐质量的问题，提出一种基于组合加权评分的Item-based协同过滤算法，以用户评分项并集作为用户相似性计算基础，并提出一种组合加权评分方法来对并集中的未评分项进行计算和填补，从而降低了数据稀疏性。实验结果表明该算法能有效提高推荐质量。
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| 关 键 词： | 数字图书馆 电子商务 Item-based协同过滤算法 组合加权评分 |
| 收稿时间： | 2008-08-05 |
| 修稿时间： | 2008-08-27 |
An Improved Item-based Collaborative Filtering Algorithm Based on Compound Weighted Rating |
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| Ma Li.An Improved Item-based Collaborative Filtering Algorithm Based on Compound Weighted Rating[J].New Technology of Library and Information Service,2008,24(11):60-64. |
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| Authors: | Ma Li |
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| Institution: | (Business College, China West Normal University, Nanchong 637002, China) |
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| Abstract: | In view of the problem that recommendation quality is seriously influenced by the sparsity of user ratings,an improved Item-based collaborative filtering algorithm based on compound weighted rating is proposed.The union of user rating items is used as the basis of similarity computing among items,moreover a compound weighted rating method is proposed to compute and complete the missing values in the union of user rating items for decreasing the sparsity.The experimental results show that the new algorithm can efficiently improve recommendation quality. |
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| Keywords: | Digital library E-commerce Item-based collaborative filtering Compound weighted rating |
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