| 一种基于Rough集理论的最近邻协同过滤算法 |
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| 引用本文： | 梁昌勇,李聪,杨善林.一种基于Rough集理论的最近邻协同过滤算法[J].情报学报,2009,28(5). |
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| 作者姓名： | 梁昌勇 李聪 杨善林 |
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| 作者单位： | 合肥工业大学管理学院,合肥,230009 |
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| 基金项目： | 国家自然科学基金重点项目，国家自然科学基金项目，国家高技术研究发展计划(863)项目，教育部科学技术研究重点项目，高等学校博士学科点专项科研基金项目 |
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| 摘 要： | 目前协同过滤被广泛应用于数字图书馆、电子商务等领域的个性化服务系统.最近邻算法则是最早提出和最主要的协同过滤推荐算法,但用户评分数据稀疏性严重影响推荐质量.针对上述问题,提出了一种基于Rough集理论的最近邻协同过滤算法,以用户评分项并集作为用户相似性计算基础,并将非目标用户区分为无推荐能力和有推荐能力两种类型;对于无推荐能力用户不再计算用户相似性以改善推荐实时性,对于有推荐能力用户则提出一种基于Rough集理论的评分预测方法来填补用户评分项并集中的缺失值,从而降低数据稀疏性.实验结果表明新算法能有效提高推荐质量.
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| 关 键 词： | 协同过滤 最近邻算法 Rough集 |
A Nearest-Neighbor Collaborative Filtering Algorithm Based on Rough Set Theory |
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| Liang Changyong,Li Cong,Yang Shanlin.A Nearest-Neighbor Collaborative Filtering Algorithm Based on Rough Set Theory[J].Journal of the China Society for Scientific andTechnical Information,2009,28(5). |
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| Authors: | Liang Changyong Li Cong Yang Shanlin |
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| Institution: | School of Management;Hefei University of Technology;Hefei 230009 |
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| Abstract: | Collaborative filtering is widely used in personalization service systems of digital library,E-commerce and so on. Nearest-neighbor algorithm is the earliest proposed and the main collaborative filtering recommendation algorithm,however its recommendation quality is seriously influenced by the sparsity of user ratings.To solve the problem,a nearest-neighbor collaborative filtering algorithm based on rough set theory is proposed.The union of user rating items is used as the basis of similarity computing amon... |
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| Keywords: | collaborative filtering nearest-neighbor algorithm rough set |
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