Sentiment Analysis using Attention Mechanism, Convolutional Neural Networks and Long Short Term Memory
Author(s):
Sarang Ajay Patel, Sanket More, Dr. Pathan Mohd. Shafi
Keywords:
Sentiment Analysis, LSTM, CNN, Attention Mechanism, VGG16, RNN
Abstract
Human sentiment analysis is a domain which has grown exponentially in recent years. There is a lot of work already published but still has scope of improvement and advancements. The aim of the project is to develop a AI/ML model which has basic and advanced capabilities of classifying the textual data, image files, etc. into accurate and automatic sentiment classification. The project mainly focuses on text and image sentiment analysis using a combination of two methods namely, LSTM and Attention-based mechanism. This research report is a deep analysis of working of this method and improving the accuracy of sentiment classification. The successful implementation of this project can introduce a wide variety of use-cases. It can have many applications ranging from customer feedback analysis, fake news identification, creditworthiness assessment. These applications may act as crucial factors, contributing towards growth of businesses and organizations.
Article Details
Unique Paper ID: 157414

Publication Volume & Issue: Volume 9, Issue 7

Page(s): 155 - 158
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