| 基于选择性预测策略的协同过滤推荐算法 |
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| 引用本文： | 刘旭东,崔蕾,陈德人.基于选择性预测策略的协同过滤推荐算法[J].武汉理工大学学报(信息与管理工程版),2014(3):365-368. |
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| 作者姓名： | 刘旭东 崔蕾 陈德人 |
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| 作者单位： | [1]烟台职业学院信息工程系,山东烟台264670 [2]浙江大学计算机科学与技术学院,浙江杭州310027 |
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| 基金项目： | 山东省高等学校科技计划基金资助项目（J12LN73）；山东省艺术科学重点科研基金资助项目（2012445）． |
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| 摘 要： | 针对传统协同过滤推荐算法在用户评分数据极端稀疏情况下无法取得令人满意的推荐质量问题，结合User-based 和Item-based 协同过滤算法思想，提出了一种基于选择性预测策略的协同过滤推荐算法，算法利用高相似度阈值来计算用户相似性和项目相似性，并通过形成用户最近邻居集和项目最近邻居集来预测填充评分矩阵。基于Movielens数据集的实验表明，改进的算法有效改善了传统协同过滤推荐算法的数据稀疏性和扩展性问题，明显提高了系统的推荐质量。
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| 关 键 词： | 协同过滤 选择性预测策略 平均绝对偏差 |
Collaborative Filtering Recommendation Algorithm Based on Selective Prediction Strategy |
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| LIU Xudong,CUI Lei,CHEN Deren.Collaborative Filtering Recommendation Algorithm Based on Selective Prediction Strategy[J].Journal of Wuhan University of Technology(Information & Management Engineering),2014(3):365-368. |
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| Authors: | LIU Xudong CUI Lei CHEN Deren |
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| Affiliation: | LIU Xudong, CUI Lei, CHEN Deren |
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| Abstract: | The user rating data in traditional collaborative filtering recommendation algorithm are extremely sparse , which results in poor recommendation quality .A recommendation algorithm based on selective prediction strategy was proposed .The user-based recommendation algorithm was combined with item -based recommendation algorithm .The user similarity and the item similarity were calculated by high similarity threshold and the user-item matrix was evaluated by finding the neighbors of users and items.The experimental results based on MovieLens data set show that the improved algorithm could solve the problem of data sparsity and scalability , and it could improve the accuracy of system recommendation significantly . |
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| Keywords: | collaborative filtering selective prediction strategy mean absolute error |
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