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The Relevance of Categories for Trusting Information Sources

机译:类别与信任信息源的相关性

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In this article, we are interested in the fact that relevance and trustworthiness of information acquired by an agent X from a source F strictly depends and derives from X's trust in F with respect to the kind of information. In particular, we are interested in analyzing the relevance of F's category as indicator for its trustworthiness with respect to the specific informative goals of X. In this article, we analyze an interactive cognitive model for searching information in a world in which each agent can be considered as belonging to a specific agent's category. We also consider variability within the canonical categorical behavior and consequent influence on the trustworthiness of provided information. The introduced interactive cognitive model also allows evaluation of the trustworthiness of a source both on the basis of its category and on past direct experience with it, thus selecting the more adequate source with respect to the informative goals to achieve. We present a computational approach based on fuzzy sets and some selected simulation scenarios together with the discussion of their more interesting results.
机译:在本文中,我们对以下事实感兴趣:代理人X从源F获取的信息的相关性和可信赖性严格取决于并从X对信息种类的信任中得出。尤其是,我们有兴趣分析F类别相对于X的特定信息目标是否可作为其可信度的指标。在本文中,我们分析了一种交互式认知模型,用于在一个可以使每个代理都参与的世界中搜索信息。被视为属于特定代理商的类别。我们还考虑了规范分类行为内的可变性,以及由此对所提供信息的可信赖性的影响。引入的交互式认知模型还允许根据来源的类别和过去对来源的直接经验来评估来源的可信度,从而根据要实现的信息目标选择更合适的来源。我们提出了一种基于模糊集和一些选定的模拟方案的计算方法,并讨论了它们更有趣的结果。

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