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A Cognitive-based Scheme for User Reliability and Expertise Assessment in QA Social Networks

机译:问答社交网络中基于认知的用户可靠性和专长评估方案

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摘要

Q&A social media has gained a great deal of attention during recent years. People rely on these sites to obtain information due to the number of advantages they offer as compared to conventional sources of knowledge (e.g., asynchronous and convenient access). However, for the same question one may find highly contradictory answers, causing ambiguity with respect to the correct information. This can be attributed to the presence of unreliable and/or non-expert users. In this work, we propose a novel approach for estimating the reliability and expertise of a user based on human cognitive traits. Every user can individually estimate these values based on local pairwise interactions. We examine the convergence performance of our algorithm and we find that it can accurately assess the reliability and the expertise of a user and can successfully react to the latter’s behavior change.
机译:问答社交媒体近年来引起了广泛关注。与传统的知识源(例如,异步访问和便利访问)相比,人们提供这些优势的原因是人们依赖这些站点​​来获取信息。但是,对于同一个问题,人们可能会找到高度矛盾的答案,从而导致对正确信息的歧义。这可以归因于存在不可靠和/或非专家用户。在这项工作中,我们提出了一种基于人类认知特征来估计用户的可靠性和专业性的新颖方法。每个用户都可以基于本地成对交互单独估计这些值。我们检查了算法的收敛性能,发现它可以准确地评估用户的可靠性和专业知识,并且可以成功应对用户的行为变化。

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