计算机科学 ›› 2018, Vol. 45 ›› Issue (12): 142-147.doi: 10.11896/j.issn.1002-137X.2018.12.022
朱引, 黄海燕
ZHU Yin, HUANG Hai-yan
摘要: 中文文本情感分析旨在发现用户对事物、事件的情感倾向,然而现有研究往往忽视了文本之间的相互联系。提出一种基于主题增强的递归自编码情感分类模型,通过将文本的主题信息融入到递归自编码模型中,使得该模型可以更深层次地考虑文本的内容信息,提高其对文本情感的理解和泛化能力。在COAE2014数据集上的实验结果表明,将所提分类模型用于情感分类任务时可获得更优的分类效果,证实了其在实际问题中的适用性与可行性。
中图分类号:
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