| 结合似然关系模型和用户等级的协同过滤推荐算法 |
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| 引用本文： | 高滢,齐红,刘杰,刘大有. 结合似然关系模型和用户等级的协同过滤推荐算法[J]. 计算机研究与发展, 2008, 45(9) |
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| 作者姓名： | 高滢 齐红 刘杰 刘大有 |
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| 作者单位： | 1. 吉林大学计算机科学与技术学院,长春,130012
2. 吉林大学符号计算与知识工程教育部重点实验室,长春,130012 |
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| 基金项目： | 国家自然科学基金，国家自然科学基金，国家高技术研究发展计划(863计划)，吉林省科技发展计划，欧盟资助项目 |
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| 摘 要： | 针对传统协同过滤推荐算法的稀疏性、扩展性问题,提出了结合似然关系模型和用户等级的协同过滤推荐算法.首先,定义了用户等级函数,采用基于用户等级的协同过滤方法,在不影响推荐质量的前提下有效提高了推荐效率,从而解决扩展性问题;然后,将其与似然关系模型相结合,使之能够综合利用用户信息、项目信息、用户对项目的评分数据,对不同用户给出不同的推荐策略,从而解决稀疏性问题,提高推荐质量.在MovieLens数据集上的实验结果表明,该算法比单纯使用基于似然关系模型或传统协同过滤技术的推荐算法,不仅推荐质量有所提高,推荐速度比传统协同过滤算法明显加快.
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| 关 键 词： | 推荐算法 协同过滤 似然关系模型 用户等级 平均绝对偏差 |
A Collaborative Filtering Recommendation Algorithm Combining Probabilistic Relational Models and User Grade |
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| Gao Ying,Qi Hong,Liu Jie,Liu Dayou. A Collaborative Filtering Recommendation Algorithm Combining Probabilistic Relational Models and User Grade[J]. Journal of Computer Research and Development, 2008, 45(9) |
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| Authors: | Gao Ying Qi Hong Liu Jie Liu Dayou |
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| Affiliation: | Gao Ying,Qi Hong,Liu Jie,, Liu Dayou(College of Computer Science , Technology,Jilin University,Changchun 130012)(Ministry of Education,Key Laboratory of Symbolic Computation , Knowledge Engineering,Changchun 130012) |
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| Abstract: | Collaborative filtering is one of successful technologies for building recommender systems. Unfortunately, it suffers from sparsity and scalability problems. To address these problems, a collaborative filtering recommendation algorithm combining probabilistic relational models and user grade (PRM-UG-CF) is presented. PRM-UG-CF has primary two parts. First, a user grade function is defined, and user grade based collaborative filtering method is used, which can find neighbors for the target user only in his n... |
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| Keywords: | recommendation algorithm collaborative filtering probabilistic relational model user grade mean absolute error (MAE) |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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