基于深度神经网络的非真诚问题分类

C. Chen
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引用次数: 2

摘要

现在人们在知乎、Quora等在线问答平台上搜索问题的答案。由于许多人依赖这些平台,过滤有争议的问题,包括但不限于仇恨言论和网络种族主义,尤为重要。虽然人力资源过于稀缺,但利用人工智能过滤掉一些有争议和侮辱性的问题是必不可少的。在这项工作中,我们提出了一种基于深度学习的分类方法来分析Quora问题的诚意,总体准确率达到95.25%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Insincere Question Classification by Deep Neural Networks
People nowadays search for answering the questions on Q&A platforms online such as Zhihu and Quora. As many rely on these platforms, filtering controversial questions, including but not limited to hate speeches and online racism, is particularly important. While human resources are too scarce, using Artificial Intelligence to filter out some disputable and insulting questions is essential. In this work, we propose a deep learning-based classification method to analyze the sincerity of questions from Quora and achieve an overall 95.25% accuracy.
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