Published Paper Details:

Today, exploiting sentiment analysis has become popular in designing recommender systems in various fields, including the restaurant and food area. The analysis of users' opinions and the extraction of their food preferences lead to the provision of personalized recommendations. The semantic approach is used to cluster the name of foods extracted from users' comments and analyze their sentiments about them. Finally, nearby open restaurants are recommended based on their similarity to user preferences. Restaurant Recommendation System is an online system to search for restaurants. The system allows visitors to browse information about the restaurants, including searching for restaurants, viewing/giving recommendations, and viewing/rating restaurants. Visitors can only view recommendations and view rating results. If the user would like to give recommendations or rate restaurants, he or she has to login or sign up. Additionally, the user can check the history of previous recommendations. In addition to customer functions, the system also provides functions to the administrator that allows to manage the contents of the site, including editing customer info, restaurants, recommendations and ratings, etc.