A comprehensive study of Natural Language processing techniques Based on Big Data

Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on understanding human language as it is written and/or spoken. To do this, specific computer programs are developed. NLP algorithms practice different syntactic and semantic analyzes to evaluate the meaning of a sentence according to grammatical rules provided beforehand, by operating a segmentation of words and groups of words or by studying the grammar of a complete sentence. To determine the meaning and the context, they compare the text in real time with all the databases at their disposal. Needing large amounts of data to identify relevant correlations On the other hand, Big Data offers a revolution in massive data management systems thanks to a set of evolving technologies like NoSQL and, Spark. In this paper, we present a comprehensive study of natural language processing (NLP) techniques based on Big Data technologies, then we compare these NLP techniques in order to show the advantage of using Big Data for the management of massive NLP data.