ML Revolution In NLP: A Review Of Machine Learning Techniques In Natural Language Processing

Document Type : Review Article


1 School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran

2 Center for Computational and Stochastic Mathematics, University of Lisbon, Portugal


In the current era, usually, people communicate with each other through the internet. This platform opens this opportunity for computer scientists to access huge information about human languages. However, this big data is unstructured from the computational point of view. Thus, computer scientists developed Natural Language Processing (NLP) methods for analyzing human language data by computers. Indeed, NLP is a way to analyze human language messages by computerized methods. On the other hand, due to the high capabilities of Machine Learning (ML), many researchers incorporated this approach in language processing techniques to improve the performance of NLP systems. In this paper, we aim to present a summarized review of the NLP techniques. considering the importance of the ML approach. Firstly, this paper introduces basic terminology for NLP. Secondly, according to the importance of ML history, the studied techniques are categorized into three groups: old-fashioned, conventional, and modern methods. The presented review in this study could be beneficial for ML and NLP reseachers in order to develop new ML techniques for NLP tasks.