| 改进的基于相关相似性的协同过滤推荐算法 |
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| 引用本文： | 赵智,冯卓楠.改进的基于相关相似性的协同过滤推荐算法[J].吉林工学院学报,2006,27(4):354-358. |
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| 作者姓名： | 赵智 冯卓楠 |
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| 作者单位： | 长春工业大学计算机科学与工程学院 吉林长春130012 |
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| 摘 要： | 分析了传统CF算法和基于项目评分的CF算法中存在的问题,对其相似性计算和推荐集选取方法进行了改进,并提出了一种优化的CF算法。实验结果表明,该算法同传统CF算法相比能显著提高推荐精度,同基于项目评分的CF算法相比能够有效减少计算复杂度。
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| 关 键 词： | 个性化推荐系统 协同过滤 相似性 推荐算法 平均绝对偏差 |
| 文章编号： | 1006-2939（2006）04-0354-05 |
| 收稿时间： | 2005-06-14 |
| 修稿时间： | 2005年6月14日 |
An adaptive algorithm of collaborative filtering recommender based on correlation similarity |
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| ZHAO Zhi,FENG Zhuo-nan.An adaptive algorithm of collaborative filtering recommender based on correlation similarity[J].Journal of Jilin Institute of Technology,2006,27(4):354-358. |
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| Authors: | ZHAO Zhi FENG Zhuo-nan |
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| Institution: | School of Computer Science and Engineering, Changehun University of Technology, Changehun 130012, China |
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| Abstract: | On the basis of analysing the deficiencies in the traditional CF algorithm and the collaborative filtering recommendation algorithm based on item rating,some improvements on the similarity calculation and recommendation selection were made and an optimized CF algorithm is given.Experimental results show that this method can noticeably provide better recommendation results than traditional CF algorithms,and can efficiently reduce the complexity of computation compared with the CF recommendation algorithm based on item rating. |
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| Keywords: | personalization recommendation system collaborative filtering similarity recommendation algorithm MAE(Mean Absolute Error) |
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