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改进相似性度量方法的协同过滤推荐算法
引用本文:吴月萍,郑建国. 改进相似性度量方法的协同过滤推荐算法[J]. 计算机应用与软件, 2011, 0(10)
作者姓名:吴月萍  郑建国
作者单位:上海第二工业大学计算机与信息学院;东华大学旭日工商管理学院;
基金项目:国家自然科学基金资助(70971020)
摘    要:协同过滤推荐技术是电子商务推荐系统中应用最成功的个性化推荐技术。但随着电子商务规模的扩大,用户数目和商品数目呈指数级的增长,传统的推荐技术其性能越来越差。因此提出一种新的相似性度量方法,自动生成权重因子,以动态组合项目属性相似度和评分相似度,形成合理的项目相似度,产生项目最近邻居,实现用户评分推荐。实验结果表明,所提的算法在一定程度上提高了推荐的稳定性和精确度,同时解决冷启动问题。

关 键 词:相似度  冷启动  协同过滤  推荐  最近邻居  

COLLABORATIVE FILTERING RECOMMENDATION ALGORITHM ON IMPROVED SIMILARITY MEASURE METHOD
Wu Yueping Zheng Jianguo. COLLABORATIVE FILTERING RECOMMENDATION ALGORITHM ON IMPROVED SIMILARITY MEASURE METHOD[J]. Computer Applications and Software, 2011, 0(10)
Authors:Wu Yueping Zheng Jianguo
Affiliation:Wu Yueping1 Zheng Jianguo2 1(School of Computer and Information,Shanghai Second Polytechnic University,Shanghai 201209,China) 2(School of Business and Management,Donghua University,Shanghai 200051,China)
Abstract:Collaborative filtering recommendation technology is the most successful personalised recommendation technology ever applied to e-commerce recommendation systems.As the scale of e-commerce expands,the magnitudes of users and commodities grow rapidly,which persistently worsens the performance of traditional recommendation technology.Therefore a new similarity measure method is put forward to automatically generate weighting factors,dynamically combine attribute similarity and score similarity,create a reason...
Keywords:Similarity Cold start Collaborative filter Recommendation Nearest neighbour  
本文献已被 CNKI 等数据库收录!
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