Paper Title
RATING FORECAST IN VIEW OF SOCIAL OPINION AND LITERARY AUDITSAbstract
Nowadays, we have seen a number of modified websites. It offers the best opportunity to share for different parts of our shopping. However, we face additional information in this issue. How important is my way about valuable information from reviews to understand user preferences and make accurate recommendations. Traditional Recommendation System (RS) consider some factors, such as user purchase records, product type, and geographic location. In this work, we recommend the prediction-based prediction method (RPS) to improve the accuracy of predictions in the processing system. First of all, we offer social-user emotional measurement and calculate the emotional of each user on items / products. Secondly, we do not consider the user\'s personal attributes, but also focus on it. After that, we consider the product\'s reputation, which can be pointed to the emotional requirement of the user\'s set that reflects the comprehensive diagnosis of the users. Lastly, we use three exercises for predicting the correct factors - In our advice system with user emotional equality, sympathetic emotional influence, and item credibility. We estimate the performance of three emotional factors on real-world databases collected from yelp. Our experimental results show that the emotional user can improve preferences, which helps improve the performance.
KEYWORDS : Recommender system, Item reputation, Reviews, Rating prediction, Sentiment influence, and User sentiment.