%0 Generic %1 zhang2015characterlevel %A Zhang, Xiang %A Zhao, Junbo %A LeCun, Yann %D 2015 %K character-level cnn gpugrant kallimachos ma-zehe neuralnet nlp %T Character-level Convolutional Networks for Text Classification %U http://arxiv.org/abs/1509.01626 %X This article offers an empirical exploration on the use of character-level convolutional networks (ConvNets) for text classification. We constructed several large-scale datasets to show that character-level convolutional networks could achieve state-of-the-art or competitive results. Comparisons are offered against traditional models such as bag of words, n-grams and their TFIDF variants, and deep learning models such as word-based ConvNets and recurrent neural networks.

@misc{zhang2015characterlevel, abstract = {This article offers an empirical exploration on the use of character-level convolutional networks (ConvNets) for text classification. We constructed several large-scale datasets to show that character-level convolutional networks could achieve state-of-the-art or competitive results. Comparisons are offered against traditional models such as bag of words, n-grams and their TFIDF variants, and deep learning models such as word-based ConvNets and recurrent neural networks.}, added-at = {2017-01-18T15:42:37.000+0100}, author = {Zhang, Xiang and Zhao, Junbo and LeCun, Yann}, biburl = {https://www.bibsonomy.org/bibtex/2f5ba3dea04c96ad7c854da7d74195ef6/albinzehe}, description = {Character-level Convolutional Networks for Text Classification}, interhash = {ec817986f91d2662694825ce51f3faa8}, intrahash = {f5ba3dea04c96ad7c854da7d74195ef6}, keywords = {character-level cnn gpugrant kallimachos ma-zehe neuralnet nlp}, note = {cite arxiv:1509.01626Comment: An early version of this work entitled "Text Understanding from Scratch" was posted in Feb 2015 as arXiv:1502.01710. The present paper has considerably more experimental results and a rewritten introduction, Advances in Neural Information Processing Systems 28 (NIPS 2015)}, timestamp = {2017-05-22T07:47:35.000+0200}, title = {Character-level Convolutional Networks for Text Classification}, url = {http://arxiv.org/abs/1509.01626}, year = 2015 }