《计算机应用研究》|Application Research of Computers

基于满意区间的协同过滤推荐算法

Satisfactory intervals similarity-based collaborative filtering recommendation algorithm

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作者 潘涛涛,朱珂,吴毅涛
机构 国家数字交换系统工程技术研究中心,郑州 450002
统计 摘要被查看 次,已被下载
文章编号 1001-3695(2017)08-2282-05
DOI 10.3969/j.issn.1001-3695.2017.08.009
摘要 针对传统协同过滤算法中用户的个性化评价标准导致评分值不能合理地表达用户对项目的偏好程度问题,提出满意区间的概念,并设计了一种协同过滤推荐算法。该算法首先根据用户各评分值的使用概率建立其与满意区间的映射关系,然后利用满意区间的期望与标准差计算用户间的相似度,最后计算用户对项目的满意度并根据该满意度预测评分值。实验结果表明,该算法能有效地解决用户的个性化评价标准问题,提高推荐准确率。
关键词 推荐系统;协同过滤;个性化;评分尺度;满意度;相似度
基金项目 国家“863”计划资助项目(2014AA01A704)
国家自然科学基金资助项目(61572520)
本文URL http://www.arocmag.com/article/01-2017-08-009.html
英文标题 Satisfactory intervals similarity-based collaborative filtering recommendation algorithm
作者英文名 Pan Taotao, Zhu Ke, Wu Yitao
机构英文名 ChinaNationalDigitalSwitchingSystemEngineering&TechnologicalR&DCenter,Zhengzhou450002,China
英文摘要 Among traditional collaborative filtering recommendation algorithms, the difference of evaluating criteria of users caused that the user’s ratings couldn’t reflect the user’s preference reasonably. In order to solve this problem, this paper proposed the concept of satisfactory intervals(SI), and designed a collaborative filtering algorithm. Firstly, the algorithm established the relationship between users’ ratings and SI. Then it calculated the similarity between users through expected value and standard deviation of SI. Finally, this algorithm rated the item by its satisfaction which was calculated before. The algorithm solved the problem of evaluating criteria by partitioning SI, which could be more reasonable for users to express their preference. Experimental results show that this algorithm can solve the problem effectively and achieve better accuracy of re-commendation obviously.
英文关键词 recommendation system; collaborative filtering; personalization; rating scale; satisfaction; similarity
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收稿日期 2016/5/19
修回日期 2016/6/27
页码 2282-2286
中图分类号 TP181
文献标志码 A