Filtering Out Unfair Ratings in Bayesian Reputation Systems
Filtering Out Unfair Ratings in Bayesian Reputation Systems
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发表时间：
2004
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通讯作者：
Andrew Whitby;A. Jøsang;J. Indulska
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作者：
Andrew Whitby;A. Jøsang;J. Indulska
信誉系统的质量取决于它作为输入接收的评级的完整性。一个根本的问题是，评级者可以对代理人进行比代理人的真实的经验更积极或更消极的评级。如果评级是由依赖方控制之外的代理人提供的，那么从先验上讲，就不可能知道评级人何时提供了这种不公平的评级。然而，通常情况下，不公平评级的统计模式与公平评级不同。本文使用这一思想，并描述了一种统计过滤技术，排除不公平的评级，并通过模拟说明其有效性。
The quality of a reputation system depends on the integrity of the ratings it receives as input. A fundamental problem is that a rater can rate an agent more positively or more negatively than the real experience with the agent would dictate. When ratings are provided by agents outside the control of the relying party, it is a priori impossible to know when a rater provides such unfair ratings. However, it is often the case that unfair ratings have a different statistical pattern than fair ratings. This paper uses that idea, and describes a statistical ltering technique for excluding unfair ratings, and illustrates its effectiveness through simulations.