TEXT CLASSFICATION USING CNN AND CNN-LSTM
2021
Text classification, language modelling, and machine translation are some of the applications.CNNs excel at retrieving local and position-invariant characteristics, but RNNs excel at classification based on a long-range semantic dependency instead of local key-value pairs.It shows out that CNNs perform admirably when used to NLP problems.The basic (Bow) model is a clear oversimplified based on faulty beliefs, but it has been the usual technique for years and has produced reasonable accuracy.The speed of CNNs is a major selling point.In this paper, Text classification is carried out by using a deep learning model that is CNN and a hybrid model using CNN-LSTM and compare the performance of two models.