Natural language processing: state of the art, current trends and challenges
This paper discusses in detail the state of the art presenting the various applications of NLP, current trends, and challenges, and presents a discussion on some available datasets, models, and evaluation metrics in NLP.
Abstract
Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. In this paper, we first distinguish four phases by discussing different levels of NLP and components of <b>N</b>atural <b>L</b>anguage <b>G</b>eneration followed by presenting the history and evolution of NLP. We then discuss in detail the state of the art presenting the various applications of NLP, current trends, and challenges. Finally, we present a discussion on some available datasets, models, and evaluation metrics in NLP.