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

融合正态分布函数相似度的协同过滤算法

Collaborative filtering algorithm fusing similarity of normal distribution function

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作者 仇国庆,马俊,赵婉滢,赵文铭
机构 重庆邮电大学 自动化学院,重庆 400065
统计 摘要被查看 次,已被下载
文章编号 1001-3695(2018)10-2920-04
DOI 10.3969/j.issn.1001-3695.2018.10.009
摘要 传统协同过滤推荐算法的相似度量方法仅考虑用户间共同评分,忽略了用户间潜在共同评分项等信息量对推荐结果的影响。针对上述问题,设计了一种正态分布函数相似度量模型,此模型考虑了用户间的共同评分、共同评分项目数以及用户的评分值,据此提出了融合正态分布函数相似度的协同过滤算法,该算法通过综合多种评分因素利用正态分布函数和修正的余弦相似度共同度量用户间的相似关系。实验结果表明,在两种数据集上与几种不同的推荐算法相比,该算法的相似度量方法提高了目标用户查找邻近用户集合的准确率,提高了系统的推荐质量。
关键词 相似度量;正态分布函数;协同过滤;邻近用户集合
基金项目 国家自然科学基金资助项目(61673079)
本文URL http://www.arocmag.com/article/01-2018-10-009.html
英文标题 Collaborative filtering algorithm fusing similarity of normal distribution function
作者英文名 Qiu Guoqing, Ma Jun, Zhao Wanying, Zhao Wenming
机构英文名 SchoolofAutomation,ChongqingUniversityofPosts&Telecommunications,Chongqing400065,China
英文摘要 The similarity measure method of traditional collaborative filtering recommendation algorithm only considered the common rating among users, ignored the effect of information such as potential common rating items among users on the recommendation results. Aiming at addressing the above problems, this paper designed a similarity metric model of normal distribution function. This model took into account the common rating between users, the number of common rating items and the user’s rating value, based on which proposed a novel collaborative filtering algorithm fusing the similarity of normal distribution function. The proposed algorithm utilized the normal distribution function and the adjusted cosine similarity to jointly measure the similarity between users by integrating multiple scoring factors. Experimental results on two data sets show that, compared to several different recommendation algorithms, the similarity measure method of the proposed algorithm improves the accuracy of searching adjacent user sets through target users and the quality of the recommendation system.
英文关键词 similarity measure; normal distribution function; collaborative filtering; adjacent user sets
参考文献 查看稿件参考文献
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收稿日期 2017/5/25
修回日期 2017/7/11
页码 2920-2923
中图分类号 TP301.6
文献标志码 A