LDA and Deep Learning: A Combined Approach for Feature Extraction and Sentiment Analysis

As everything is available in online, had made the lives of common people to look towards the e-commerce applications for purchasing their general needs. People now-a-days want to share their preferences after receiving the goods as reviews. These reviews have a direct impact on the product for the customers to decide whether to buy or not. Besides, the huge information available in user reviews it is very difficult for the user to identify the exact preferences of good or bad based on the feature for what he is searching. So, extracting user preferences and item properties is very useful. This paper introduces an approach to extract the most important aspects from the opinions expressed in the input text using various machine learning and deep learning techniques. Further, it describes the topic modelling technique like LDA for extracting topics and uses deep learning for integrating the topics/features from topic modeling which is a meaningful approach for better understanding of reviews.