开发者对机器学习了解多少:StackOverflow上的ML讨论研究

A. A. Bangash, Hareem Sahar, S. Chowdhury, A. W. Wong, Abram Hindle, Karim Ali
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引用次数: 36

摘要

机器学习是人工智能的一个分支,现在在软件工程界很流行,并成功地用于错误预测和软件开发工作量估计等问题。然而,开发人员对机器学习的理解并不清楚,我们需要进行调查,以了解教育者应该关注什么,以及不同的在线编程讨论社区如何更有帮助。我们使用SOTorrent数据集对Stack Overflow (SO)机器学习相关帖子进行了研究。我们发现,一些机器学习主题比其他主题被讨论得更多,而另一些主题则需要更多的关注。我们还发现,使用潜在狄利克雷分配(Latent Dirichlet Allocation, LDA)的主题生成可以建议更合适的标签,使机器学习帖子更可见,从而有助于从SO等网站获得即时反馈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What do Developers Know About Machine Learning: A Study of ML Discussions on StackOverflow
Machine learning, a branch of Artificial Intelligence, is now popular in software engineering community and is successfully used for problems like bug prediction, and software development effort estimation. Developers' understanding of machine learning, however, is not clear, and we require investigation to understand what educators should focus on, and how different online programming discussion communities can be more helpful. We conduct a study on Stack Overflow (SO) machine learning related posts using the SOTorrent dataset. We found that some machine learning topics are significantly more discussed than others, and others need more attention. We also found that topic generation with Latent Dirichlet Allocation (LDA) can suggest more appropriate tags that can make a machine learning post more visible and thus can help in receiving immediate feedback from sites like SO.
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