A Comprehensive Analytical Study of Traditional and Recent Development in Natural Language Processing
Journal: International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE) (Vol.10, No. 5)Publication Date: 2021-10-13
Authors : Aditya Datta Biswajit Jena Amiya Kumar Dash Roshni Pradhan;
Page : 3009-3019
Keywords : Natural Language Processing (NLP); Tokenization; Deep Learning; Recurrent Neural network (RNN); Long Short-Term Memory (LSTM); Bidirectional Recurrent Neural Network (BiRNN).;
Abstract
This paper acts as a comprehensive analytical study of natural language processing (NLP) and provides a briefing of the most prominent astounding reforms of the field over a good chunk of time. It covers even the future research insights and most relevant features, which act as a result of the discussed concepts or research, until this paper's reading point. This paper starts with covering the most basic concepts of text cleaning, such as tokenization, the importance of stop words, etc., to concepts such as sequence modeling, speech recognition, the effect of quantum computing concepts in Natural Language Processing, and so on. The current development of deep neural networks, which is the current trend in artificial intelligence, always gives NLP a cutting-edge technology, also covered in this paper. This paper will also emphasize that it covers the broad area of explanations to the concepts to guide learners or researchers to have an excellent overall understanding of the field.
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Last modified: 2021-10-13 17:04:49