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现代图书情报技术  2015, Vol. 31 Issue (9): 38-45    DOI: 10.11925/infotech.1003-3513.2015.09.06
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
一种引入间接信任关系的改进协同过滤推荐算法
吴应良, 姚怀栋, 李成安
华南理工大学电子商务系 广州 510006
An Improved Collaborative Filtering Recommendation Algorithm with Indirect Trust Relationship
Wu Yingliang, Yao Huaidong, Li Cheng'an
E-Business Department, South China University of Technology, Guangzhou 510006, China
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摘要 

[目的]解决传统协同过滤推荐算法中由于数据稀疏性等原因而导致的推荐质量恶化问题, 需要对协同过滤推荐算法的推荐机制进行改进优化。[方法]利用社会网络分析中的凝聚子群分析技术挖掘隐含在信任网络中的间接信任关系, 与直接信任加权融合成综合信任度, 并将其融入用户相似度计算中。[结果]实验结果显示, 信任关系中间接信任不容忽视, 当间接信任以35%的比例与直接信任融合时, 推荐效果比仅引入直接信任关系有进一步提升。[局限]在考虑信任网络中的间接信任时, 忽略了用户之间多中介节点的间接信任情况对推荐精度的影响。[结论]引入间接信任关系的软集成可以提高协同过滤算法的推荐准确性。

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Abstract

[Objective] In traditional collaborative filtering algorithms, the issues such as data sparsity may make the quality of recommendation worse. This paper attempts to solve it by optimizing the recommendation mechanisms. [Methods] This paper uses cohesive subgroup analysis techniques to identify indirect trust relationship in trust networks, and combines with direct trust relationship to generate an integrated trust, which is used to calculate the user similarity in the new collaborative filtering recommendation algorithm. [Results] Experimental results show that the ultimate trust combining 35% direct and 65% indirect relationship can improve the accuracy of CF algorithms, and compared with only using direct trust relationship, the indirect trust relationship could not be ignored. [Limitations] When considering the indirect trust in the trust network, this paper ignores the impact of more intermediate nodes between two users. [Conclusions] Soft integration of indirect trust relationship can improve the recommendation accuracy of collaborative filtering algorithms.

收稿日期: 2015-01-04     
:  TP301  
基金资助:

本文系国家社会科学基金项目“基于关联数据的政府数据开放研究”(项目编号:14BTQ009)、省部产学研结合项目——基地建设专项项目“广东现代服务业公共支撑平台的开发与应用研究”(项目编号:2009B090200062)和广州市花都区科技计划重点专项项目“石头记电子商务平台建设”(项目编号:HD12ZD-008)的研究成果之一。

通讯作者: 姚怀栋, ORCID: 0000-0002-9286-8661, E-mail: yaohd_scut@126.com。     E-mail: yaohd_scut@126.com
作者简介: 作者贡献声明:吴应良:提出研究思路,设计研究方案,论文最终版本修订;姚怀栋,李成安:进行实验;姚怀栋:采集、清洗和分析数据;吴应良,姚怀栋,李成安:论文起草。
引用本文:   
吴应良, 姚怀栋, 李成安. 一种引入间接信任关系的改进协同过滤推荐算法[J]. 现代图书情报技术, 2015, 31(9): 38-45.
Wu Yingliang, Yao Huaidong, Li Cheng'an. An Improved Collaborative Filtering Recommendation Algorithm with Indirect Trust Relationship. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2015.09.06.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2015.09.06

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