NLP Review: Architectures, Techniques, Applications and Challenges
Ankit Sirmorya, Sowmyashree Ramesh Kumar, Mehul Vishal Sadh · International Journal of Computer Applications · 2022
The natural language processing (NLP) field entails the application of a broad range of computational approaches to the automatic analysis and representation of human language.It's a field of artificial intelligence in which computers analyze, understand, and derive meaning information from human language in a smart and useful way.A large percentage of NLP applications are used to organize and structure knowledge in order to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation.The paper goes through different NLP architectures that can perform such tasks.Various architectures have been discussed in detail, such as CNN, RNN, LSTM, and GRU.Additionally, we cover NLP Techniques such as Morphological Analysis, Semantic Analysis, Sentiment Analysis, Keyword Extraction, Stemming, and Lemmatization.There are also several limitations of this methodology.Almost every industry uses NLP.NLP plays a major role in many fields like Health care, Information Retrieval, and Web mining.We finally gave a brief review on different NLP topics and future research.