计算机科学 ›› 2018, Vol. 45 ›› Issue (10): 37-42.doi: 10.11896/j.issn.1002-137X.2018.10.007
• 2018 年中国粒计算与知识发现学术会议 • 上一篇 下一篇
张紫茵, 张恒汝, 徐媛媛, 秦琴
ZHANG Zi-yin, ZHANG Heng-ru, XU Yuan-yuan, QIN Qin
摘要: 数据稀疏性是目前协同过滤面临的主要挑战之一。用户间的信任关系为推荐系统提供了有用的附加信息。已有工作主要采用直接信任关系作为附加信息,对间接信任关系考虑得较少。针对这一情况,提出一种融合直接和间接的用户非对称信任关系的推荐算法(ATRec)。首先,构建一种信任传递机制,并利用该机制获得用户间的间接非对称信任关系。其次,根据直接和间接非对称信任关系获得每个用户的信任集合。最后,利用信任集合、最近邻的评分和好评阈值计算出商品的受欢迎程度,进而获得对用户的top-N推荐列表。在真实数据集上的实验结果表明,该算法比主流的推荐算法在top-N推荐性能上有更好的表现。
中图分类号:
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