Papers
arxiv:1509.01626
Character-level Convolutional Networks for Text Classification
Published on Sep 4, 2015
Abstract
Character-level convolutional networks achieve state-of-the-art results for text classification compared to traditional and word-based models.
AI-generated summary
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.