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Which Step Do I Take First? Troubleshooting with Bayesian Models

机译:我应该先走哪一步?贝叶斯模型故障排除

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摘要

Online discussion forums and community question-answering websites provide one of the primary avenues for online users to share information. In this paper, we propose text mining techniques which aid users navigate troubleshooting-oriented data such as questions asked on forums and their suggested solutions. We introduce Bayesian generative models of the troubleshooting data and apply them to two interrelated tasks (a) predicting the complexity of the solutions (e.g., plugging a keyboard in the computer is easier compared to installing a special driver) and (b) presenting them in a ranked order from least to most complex. Experimental results show that our models are on par with human performance on these tasks, while outperforming baselines based on solution length or readability.
机译:在线讨论论坛和社区问答网站为在线用户共享信息提供了主要途径之一。在本文中,我们提出了文本挖掘技术,该技术可帮助用户浏览面向故障排除的数据,例如论坛上提出的问题及其建议的解决方案。我们介绍故障排除数据的贝叶斯生成模型,并将其应用于两个相互关联的任务(a)预测解决方案的复杂性(例如,与安装专用驱动程序相比,将键盘插入计算机要容易得多),以及(b)将它们显示在从最低到最复杂的排名顺序。实验结果表明,我们的模型在执行这些任务时可以与人类表现相提并论,而基于解决方案的长度或可读性,它们的表现要优于基线。

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