| 基于用户角色与行为的协同过滤推荐算法 |
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| 引用本文： | 尹柱平,李幼平.基于用户角色与行为的协同过滤推荐算法[J].桂林电子科技大学学报,2011,31(3):230-233. |
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| 作者姓名： | 尹柱平 李幼平 |
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| 作者单位： | 尹柱平,Yin Zhuping(桂林电子科技大学,商学院,广西,桂林,541004);李幼平,Li Youping(桂林航天工业高等专科学校,广西,桂林,541004) |
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| 摘 要： | 针对传统协同过滤推荐算法中存在评分数据稀疏性问题,以稀疏的用户打分来确定用户间的相似性可能并不准确.为此,提出了以用户行为对应一定分值代替空缺评分的方法来修正用户I-U评分矩阵,并基于用户角色以权重系数K来约束最近邻的计算.实验表明,改进的算法具有更优的推荐质量.
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| 关 键 词： | 协同过滤 I-U评分矩阵 最近邻 用户角色 用户行为 |
Collaborative filtering algorithm based on users role and its behavior |
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| Yin Zhuping,Li Youping.Collaborative filtering algorithm based on users role and its behavior[J].Journal of Guilin Institute of Electronic Technology,2011,31(3):230-233. |
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| Authors: | Yin Zhuping Li Youping |
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| Affiliation: | Yin Zhuping1,Li Youping2(1.School of Business,Guilin University of Electronic Technology,Guilin 541004,China,2.Guilin College of Aerospace Technology,China) |
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| Abstract: | Aiming at sparsity of score data in the traditional collaborative filtering algorithm,the similarity among users base on this sparse ratings may not be accurate.For this reason,a collaborative filtering algorithm based on fixed I-U score matrix and weighted coefficient K to constrain the nearest neighbor calculation was proposed.The fixed I-U score matrix was presented by a certain percentile of user behavior instead of vacancies scoring.The weighted coefficient K was based on user role.Experiments show tha... |
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| Keywords: | collaborative filtering I-U score matrix nearest neighbor user role user behavior |
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