• Sowmya N
• Veena V
• Laxmidevi H M
• Manjunath R

Natural Language Processing (NLP) is a subfield of artificial intelligence (AI). It helps machines process and understand the human language so that they can automatically perform repetitive tasks. Classification of text and recognition is considered as a fundamental research area in the field of natural language processing, which is a discipline that merges computer, mathematics, and linguistic experience. In the context of the big data era, how to effectively classify text information in the face of a sea of text-based data is the focus of current research. This paper describes the theoretical knowledge of text classification concepts, text representation methods and text classifiers. Firstly, the basic concepts of text classification and the classification process are introduced. Then the model structures of convolutional and recurrent neural networks and their variants are introduced, followed by the structure and implementation principles of two classical word embedding models, Word2vec and BERT.

Natural Language Processing, Text Classification, Models, Word2vec, BERT

"A Study on Text Mining Using Natural Language Processing and Artificial Intelligence Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.j706-j711, July-2023, Available :http://www.jetir.org/papers/JETIR2307989.pdf

"A Study on Text Mining Using Natural Language Processing and Artificial Intelligence Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppj706-j711, July-2023, Available at : http://www.jetir.org/papers/JETIR2307989.pdf