Design of A Recurrent Neural Network Model for Machine Reading Comprehension
Uttam Singh, Shweta Kedas, Sikakollu Prasanth, Arun Kumar, Vijay Bhaskar Semwal, Vinay Anand Tikkiwal · Procedia Computer Science · 2020
Reading paragraphs, understanding the related questions and answering them has always been a difficult task for the machines. Humans have the capability to understand the logic and meaning of a question and answer it to maintain a proper mode of interaction. But for machines, this is a complex task. The main focus of this research work is to explore the various machine learning and neural networks based techniques to develop and train a model on context of paragraphs related questions and answers and then test the model on an user given paragraph and question. This paper presents a thorough understanding of data analysis of the SQuAD data set and word embedding applied on the questions and answers of training set of the SQuAD data set.