@inproceedings{f09217e640754d7ba299fa2626ea7dab,
title = "A convolutional attention model for text classification",
abstract = "Neural network models with attention mechanism have shown their efficiencies on various tasks. However, there is little research work on attention mechanism for text classification and existing attention model for text classification lacks of cognitive intuition and mathematical explanation. In this paper, we propose a new architecture of neural network based on the attention model for text classification. In particular, we show that the convolutional neural network (CNN) is a reasonable model for extracting attentions from text sequences in mathematics. We then propose a novel attention model base on CNN and introduce a new network architecture which combines recurrent neural network with our CNN-based attention model. Experimental results on five datasets show that our proposed models can accurately capture the salient parts of sentences to improve the performance of text classification.",
author = "Jiachen Du and Lin Gui and Ruifeng Xu and Yulan He",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.; 6th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2017 ; Conference date: 08-11-2017 Through 12-11-2017",
year = "2018",
doi = "10.1007/978-3-319-73618-1\_16",
language = "英语",
isbn = "9783319736174",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "183--195",
editor = "Xuanjing Huang and Jing Jiang and Dongyan Zhao and Yansong Feng and Yu Hong",
booktitle = "Natural Language Processing and Chinese Computing - 6th CCF International Conference, NLPCC 2017, Proceedings",
address = "德国",
}