Document worth reading: “Advances in Natural Language Question Answering: A Review”

Question Answering has simply currently obtained extreme consideration from artificial intelligence communities due to the developments in learning utilized sciences. Early question answering fashions used rule-based approaches and moved to the statistical technique to take care of the vastly on the market information. However, statistical approaches are confirmed to underperform in coping with the dynamic nature and the variation of language. Therefore, learning fashions have confirmed the aptitude of coping with the dynamic nature and variations in language. Many deep learning methods have been launched to question answering. Most of the deep learning approaches have confirmed to realize higher outcomes in comparability with machine learning and statistical methods. The dynamic nature of language has profited from the nonlinear learning in deep learning. This has created excellent success and a spike in work on question answering. This paper discusses the successes and challenges in question answering question answering methods and strategies that are used in these challenges. Advances in Natural Language Question Answering: A Review