Learning Automata Based Sentiment Analysis for recommender system on cloud

The development of personalized recommendation systems has been an interesting research topic after the rapid evolution in social networking sites. In this paper, we propose a recommendation system using Learning automata (LA) and sentiment analysis. LA is used to optimize the recommendation score produced by the proposed system using sentiment analysis. The proposed Learning Automata-Based Sentiment Analysis System (LASA) recommends the places nearby the current location of the users by analyzing the feedback from the places and thus calculating the score based on it. Experiments performed by us indicate that by using LA, we can improve the performance of the proposed system, and, thus, help a user to find a specific location according to the need.