Expertise Analysis in a Question Answer Portal for Author Ranking

Lin Chen, R. Nayak
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引用次数: 21

Abstract

An online question answering (QA) portal provides users a way to socialize and help each other to solve problems. The majority of the online question answer systems use user-feedback to rank userspsila answers. This way of ranking is inefficient as it involves ongoing efforts by the users and is subjective. Currently researchers have utilized link analysis of user interactions for this task. However, this is not accurate in some circumstances. A detailed structural analysis of an online QA portal is conducted in this paper. A novel approach based on userspsila reputation reflecting the usage patterns is proposed to rank and recommend the user answers. The method is compared with a popular link topology analysis method, HITS. The result of the proposed method is promising.
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面向作者排名的问答门户中的专家分析
在线问答(QA)门户为用户提供了一种社交和相互帮助解决问题的方式。大多数在线问答系统使用用户反馈来对用户的答案进行排名。这种排名方式效率低下,因为它涉及用户的持续努力,而且是主观的。目前,研究人员已经利用用户交互的链接分析来完成这项任务。然而,这在某些情况下是不准确的。本文对在线QA门户网站进行了详细的结构分析。提出了一种基于反映用户使用模式的用户信誉对用户答案进行排序和推荐的新方法。该方法与一种流行的链路拓扑分析方法HITS进行了比较。该方法的结果是有希望的。
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