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基于改进自编码器的文本分类算法
Authors
潘竹虹
许卓斌
郑海山
Publication date
15 June 2018
Publisher
Abstract
词的向量化表达是文本挖掘应用的必要前提。为了改善自编码器在词嵌入中的效果,提高文本分类的准确性,提出了一种改进的自编码器并将其用于文本分类。在传统自编码器的基础上,在隐藏层加入了一个全局调整函数,其将绝对值小的特征值调整到绝对值大的特征值上,实现了隐藏层特征向量的稀疏化。得到调整后的特征向量之后,采用全连接神经网络进行文本分类。在20news数据集上的实验结果表明,所提方法具有更好的词向量嵌入式效果,并且在文本分类中也具有更好的效果。赛尔网络下一代互联网技术创新项目(NGII20160410)资
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Last time updated on 10/06/2020