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Document-Based Sentiment Analysis Employing BERT-Deep Learning Method
Abstract
In this work an integrated deep learning approach is presented for document-based sentiment analysis. To categorize the polarity of the sentiments into positive, negative, and neutral, deep learning method is integrated with document-based sentiment analysis. The Convolutional Neural Network (CNN) considers the customers' review as a document and classifies them based on sentiments. Transfer learning-based deep learning model has been implemented in this work for natural language processing. Transfer learning-based Bidirectional Encoder Representations from Transformer (BERT) model has given better results than the other methods. This work applied a Bidirectional Encoder Representations from Transformer – Convolutional Neural Network (BERT-CNN) for sentiment classification. BERT is used to capture feature representation and deep learning layers for extraction, followed by softmax classification. The proposed approach achieved 95% accuracy on IMDB and Amazon reviews, demonstrating practical effectiveness.
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