【摘 要】
:
文本自动分类是自然语言理解与信息检索的研究重点和技术核心,一直备受自然语言处理研究人员的关注。文章以基于深度学习的文本分类技术为研究背景,介绍其分类的过程、文本的
【基金项目】
:
国家电网公司总部科技项目资助“用电类运营大数据质量评估及改进关键技术研究”(SGRIJSKJ[2015]1029)
论文部分内容阅读
文本自动分类是自然语言理解与信息检索的研究重点和技术核心,一直备受自然语言处理研究人员的关注。文章以基于深度学习的文本分类技术为研究背景,介绍其分类的过程、文本的分布式表示以及基于深度学习神经网络的文本分类模型,并以情感分析、主题分类为任务对几种典型的模型结构进行了实验和分析。实验结果表明,在中英文不同的测试数据集上,基于深度学习的文本分类方法均可以得到83%以上的准确率,具有很好的分类效果。
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