Enhancing Review System of Restaurant Using Deep Learning Approach for Sentiment Analysis

In this digital era, Recommendation Systems play a crucial role in consumer decision-making. Prevalence of fake reviews or lack of reviews on restaurant recommendation websites may tend to mislead the consumers and cause negative conviction on the reputation of restaurants. This research study involves in exploiting collected rich datasets, pre-trained word embedding, analyzing facial expressions using sentiment analysis, implementing neural network architectures and deep learning models in enhancing the accuracy of recommendation websites by providing personalized suggestions based on real-time feedback from rich data. Overall, this novel strategy guarantees to transform the way consumers explore and select restaurants by creating a more dynamic and adaptable approach in restaurant recommendation domain.