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Individual Opinions Versus Collective Opinions in Trust Modelling

机译:个人意见与信任建模中的集体意见

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Social web permits users to acquire information from anonymous people around the world. This leads to a serious question about the trustworthiness of the information and the sources. During the last decade, numerous models were proposed to adapt social trust to social web. These models aim to assist the user in becoming able to state his opinion about the acquired information and their sources based on their trustworthiness. Usually, opinions can be based on two mechanisms to acquire knowledge: evaluating previous interactions with the source (individual knowledge), and word of mouth mechanism where the user relies on the knowledge of his friends and their friends (collective knowledge). In this paper, we are interested in the impact of using each of these mechanisms on the performance of trust models. Subjective logic (SL) is an extension of probabilistic logic that deals with the cases of lack of evidence. It supplies framework for modelling trust on the web. We use SL in this paper to build and compare two trust models. The first one gives priority to individual opinions, and uses collective opinions only in the case of absence of individual opinions. The second considers only collective opinions permanently, so it always provides the most complete knowledge that leads to improving the performance of the model.
机译:社交网络允许用户从世界各地的匿名人员获取信息。这导致关于信息和来源的可信度的严重问题。在过去十年中,众多模型是提出适应社会信任的社交网络。这些模型的目标是帮助用户能够在他们的可靠性方面讨论他对所收购信息及其来源的看法。通常,意见可以基于获得知识的两种机制:评估以前与源(个人知识)的互动,以及用户依赖他朋友和他们的朋友的知识(集体知识)的嘴机制的话语。在本文中,我们对使用这些机制对信任模型的性能的影响感兴趣。主观逻辑(SL)是概率逻辑的延伸,这些逻辑涉及缺乏证据的情况。它提供了用于对网上建模信任的框架。我们在本文中使用SL来构建和比较两个信任模型。第一个优先考虑个人意见,只在没有个人意见的情况下使用集体意见。第二次认为只有集体意见永久性,因此它总是提供最完整的知识,导致提高模型的性能。

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