Sentiment analysis and machine translation-based NLP for human language and machine understanding

Abstract

Natural Language Processing is concerned with the way in which computers and other machine systems analyze, understand, and generate language that is human in nature. In this paper, the scope of Natural Language Processing (NLP) is analyzed, its origins, the methods used in it, then its practical use and most complex issues are introduced. The sphere of NLP is rather wide and includes rule-based, statistical and deep learning techniques. The practical applications of these methodologies are demonstrated by the results from recent applications in sentiment analysis, machine translation and text summarization. Finally, the advances already achieved and potential future trends in NLP research are covered in the context of a rapidly developing field.