Character-level Convolutional Networks for Text Classification
Abstract - This article offers an empirical exploration of the use of character-level convolutional networks (ConvNets) for text classification. We constructed several largescale 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 a bag of words, n-grams and their TFIDF variants, and deep learning models such as word-based ConvNets and recurrent neural networks.
Dataset - http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html
Problem Statement -
- Implement using PyTorch
- Use the AG’s corpus of news articles dataset
- Implement word-based ConvNets method