CNN for Text-Based Multiple Choice Question Answering
Akshay Chaturvedi, Onkar Pandit, Utpal Garain · 2018
The task of Question Answering is at the very core of machine comprehension.In this paper, we propose a Convolutional Neural Network (CNN) model for textbased multiple choice question answering where questions are based on a particular article.Given an article and a multiple choice question, our model assigns a score to each question-option tuple and chooses the final option accordingly.We test our model on Textbook Question Answering (TQA) and SciQ dataset.Our model outperforms several LSTM-based baseline models on the two datasets.