DEEP LEARNING TECHNIQUES ON TEXT CLASSIFICATION IN SOCIAL HEALTH NETWORK

Abstract

Text classification technique used for classifying the unstructured and structured data available abundantly in social health network. Using the deep learning techniques, text classifier can label the text into different classes with a good accuracy. Text classifier uses different techniques available in deep learning namely, CNN (Convolutional Neural Networks) and RNN (Recurrent Neural Networks). The existing model has immense data which is not arranged properly, and also contains many unstructured forms of data, which is a quite difficult one for analysing. The proposed model uses Deep Learning (DL) RNN (Recurrent Neural Network) technique consist
of yielding good results by using the models of pattern recognition for social healthcare networks. The main intention of text classification model is to provides an insight for training the data and to classify the text by analyzing and extracting the raw input and produce the output. Overall, the purpose of text classification model is to enhance the performance of the text classifier based on effectiveness to improve accuracy and text processing speed by using a suitable methodology in order produce the promising results in the future.