Resisting Collusion by Game in Culture Web

Yu Bao, Tianjie Cao, Guosun Zeng
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引用次数: 73

Abstract

State of the culture web allow the users to aggregate information from many culture heritages' sources or buy the foreign culture products. In these websites, reputation systems, a proved useful mechanism, is introduced to help people to decide which information deserved to trust. To maintain the overall credibility of the information, users are confronted with assessing the reliability of information from different sources. This paper presents anti-collusion algorithm, a collusive group recognition method based on game theory. In reputation systems, users forming collusive group tend to increase theirs own reputations by abusing evaluation of other users' behaviors. Anti-collusion algorithm makes a good use of the game between the members of collusive group, who have to form a special pattern of profit distribution not only on income of reputation but also on distribution of profit if they want to get the benefits from collusion. In order to promote capabilities of the system, anti-collusion algorithm will be adopted to distinguish these groups in terms of the special pattern.
用游戏抵制文化网络中的合谋
文化网络的状态允许用户从许多文化遗产资源中收集信息或购买外国文化产品。在这些网站中,信誉系统(一种被证明有用的机制)被引入,以帮助人们决定哪些信息值得信任。为了保持信息的整体可信度,用户需要评估来自不同来源的信息的可靠性。本文提出了一种基于博弈论的合谋群体识别方法——反合谋算法。在声誉系统中,形成串通群体的用户往往通过滥用对其他用户行为的评价来提高自己的声誉。反合谋算法很好地利用了合谋集团成员之间的博弈,要想从合谋中获得利益,不仅要在名誉收益上,还要在利润分配上形成一种特殊的利益分配模式。为了提高系统的性能,将采用反合谋算法,根据其特殊的模式来区分这些组。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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