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首页> 外文会议>Privacy, Security, Trust and the Management of e-Business, 2009. CONGRESS '09 >Synergies of Different Reputation Systems: Challenges and Opportunities
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Synergies of Different Reputation Systems: Challenges and Opportunities

机译：不同声誉系统的协同作用：挑战与机遇

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摘要

Reputation is a well established means to determine trustworthiness in online systems in various contexts, e.g. online transactions, product recommendation, e-mail spam fighting, etc. However, typically these reputation systems are ``closed'' outside of the community: the set of participants, their possible actions, their evaluation and the mechanism to derive trust evaluations are predetermined in the system design. Therefore, existing information is hardly reused and emerging online communities have a "cold" start regarding trustworthiness. In this paper, we discuss the various opportunities that arise by combining reputation information from different communities and provide a detail discussion on related challenges, namely identification, mapping of reputation semantics, contextual distance, reputation disclosure (dis) incentives and privacy. For example, the critical issue of identification can more effectively be dealt with based on entity-matching and the social structure of different systems. Furthermore, we argue and theoretically prove that even na"{i}ve combinations of reputation values from different communities can result in a system capable of detecting misbehavior more effectively than the individual reputation mechanisms themselves under certain conditions on reputation semantics.
机译：信誉是一种在各种情况下（例如，在线交易）确定在线系统中可信度的成熟方法。在线交易，产品推荐，打击电子邮件垃圾邮件等。但是，通常，这些信誉系统在社区外部是“封闭的”：参与者的集合，他们可能采取的行动，他们的评估以及得出信任评估的机制是在系统设计中预先确定。因此，现有信息很难再利用，新兴的在线社区在可信赖性方面也有“冷”的开端。在本文中，我们讨论了通过组合来自不同社区的信誉信息而产生的各种机会，并提供了有关相关挑战的详细讨论，即识别，信誉语义映射，上下文距离，信誉披露（dis）动机和隐私。例如，基于实体匹配和不同系统的社会结构，可以更有效地处理识别的关键问题。此外，我们争论并从理论上证明，即使在不同的声誉信誉条件下，即使来自不同社区的声誉值的简单组合也可以形成一个比个别声誉机制本身更有效地检测不良行为的系统。

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