Teaching Assistant
Paper ID: 113


  • CNN

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 -

  1. Implement using PyTorch
  2. Use the AG’s corpus of news articles dataset
  3. Implement word-based ConvNets method