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回答问题专家群体的演变

Evolution of Experts in Question Answering Communities
课程网址: http://videolectures.net/icwsm2012_pal_evolution/  
主讲教师: Aditya Pal
开课单位: 明尼苏达大学
开课时间: 2012-07-06
课程语种: 英语
中文简介:
社区问答(CQA)服务由于少数高活跃用户(通常称为专家)而蓬勃发展,他们提供大量高质量的有用答案。了解专家之间的时间动态和互动可以提供关于社区成员如何随时间演变的关键见解。在本文中,我们提出了CQA专家的时间研究,并分析了他们的行为模式随时间的变化。此外,使用无监督的机器学习方法,我们展示了有助于我们区分专家的有趣的进化模式。使用监督分类方法,我们表明基于用户进化数据的模型在专家识别方面比忽略进化的模型更有效。我们在两个大型在线CQA上进行实验,以显示我们提出的方法的一般性。
课程简介: Community Question Answering (CQA) services thrive as a result of a small number of highly active users, typically called experts, who provide a large number of high quality useful answers. Understanding the temporal dynamics and interactions between experts can present key insights into how community members evolve over time. In this paper, we present a temporal study of experts in CQA and analyze the changes in their behavioral patterns over time. Further, using unsupervised machine learning methods, we show the interesting evolution patterns that can help us distinguish experts from one another. Using supervised classification methods, we show that the models based on evolutionary data of users can be more effective at expert identification than the models that ignore evolution. We run our experiments on two large online CQA to show the generality of our proposed approach.
关 键 词: 社区问答; 时间研究; 机器学习方法
课程来源: 视频讲座网
最后编审: 2019-04-27:lxf
阅读次数: 63