An analytical study of Natural Language Processing in context with Machine Learning

Abstract

Natural Language processing study has reached some extent where distinct machine learning algorithms were implemented to obtain better leads to text classification. This paper presents much previous research works in this field of interest. It discusses the different techniques used for text classification so far and summarizes the various methods' benefits and disadvantages. It is observed that each one of the algorithms works well, but some strategies outperform others. Most of the algorithms are often improved by careful selection of the features which play an essential role within the learning of an algorithm.