通过传播信任和不信任来增强推荐

Patricia Victor, C. Cornelis, M. D. Cock
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引用次数: 10

摘要

事实证明,在推荐系统的用户之间建立信任网络有利于提高推荐的质量和数量。此外,涉及不信任可以提供如何处理特定推荐以及防止推荐攻击的额外线索,但到目前为止,这个方向还没有得到彻底的探索。在本文中,我们提倡对RSs使用信任模型,其中信任分数是(信任,不信任)对,从一个双边格子中提取。我们设计了一个实验装置来深入了解电影RS中的信任传播问题,并提出了两个信任分数传播算子,每个算子都反映了不同的用户行为模式或特征
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Recommendations through Propagation of Trust and Distrust
The incorporation of a trust network among the users of a recommender system (RS) proves beneficial to the quality and amount of recommendations. Involving also distrust can offer additional clues how to handle specific recommendations as well as protection against recommendation attacks, yet this direction has not been thoroughly explored so far. In this paper, we advocate the use of a trust model for RSs in which trust scores are (trust,distrust)-couples, drawn from a bilattice. We design an experimental setup to get insight into the trust propagation problem in a movie RS and propose two trust score propagation operators, each reflecting a distinct user behaviour pattern or profile
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