| 基于专家信任优先的协同过滤推荐算法 |
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| 引用本文： | 景民昌,唐弟官,于迎辉.基于专家信任优先的协同过滤推荐算法[J].图书情报工作,2012,56(11):105-108. |
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| 作者姓名： | 景民昌 唐弟官 于迎辉 |
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| 作者单位： | 1. 中国科学院研究生院;2. 中国石油大学图书馆; |
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| 基金项目： | 北京高校图书馆科研基金项目“基于社会网络拓展图书馆服务领域的研究探索” |
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| 摘 要： | 针对传统协同过滤推荐算法的不足，依据现实生活经验，认为在协同过滤推荐过程中考虑用户的专家信任因素十分必要。详细阐述专家信任的概念以及利用用户评分数据计算专家信任度的方法，提出一种基于专家优先信任的协同过滤推荐算法。在公开数据集GroupLens上的实验结果表明，该算法预测用户评分的精度和成功率都明显优于传统的最近邻法。
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| 关 键 词： | 协同过滤 信任度 最近邻 专家信任优先 |
| 收稿时间： | 2011-09-29 |
| 修稿时间： | 2011-12-02 |
A Recommending Method Based on Expert Prior Trust in Collaborative Filtering |
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| Jing Minchang,Tang Diguan,Yu Yinghui.A Recommending Method Based on Expert Prior Trust in Collaborative Filtering[J].Library and Information Service,2012,56(11):105-108. |
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| Authors: | Jing Minchang Tang Diguan Yu Yinghui |
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| Institution: | 1. Graduate University of Chinese Academy of Sciences,;2. Library of China University of Petroleum,; |
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| Abstract: | In view of the limitations of traditional collaborative filtering recommendation algorithm and according to real life experience,this paper argues that integrating expert factor of user with collaborative filtering is necessary,elaborates on the concept of expert trust and its computing method by using rating data,and proposes a collaborative filtering algorithm based on expert prior trust.The experimental results on an open dataset named GroupLens show that,the algorithm in prediction accuracy and success rates are superior to the traditional nearest neighbor method. |
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| Keywords: | collaborative filtering trustworthiness nearest neighbor expert prior trust |
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