Social Recommender System Using Skyline Query and Reciprocal Scoring Technique
Poonam Rani · IOSR Journal of Engineering · 2017
With the internet being flooded with various social networking sites, e-commerce websites, video streaming sites, news websites; a naive user would want to access relevant data which could be possibly of his/her interest and to achieve this, services such as a recommender system is required, which uses not only user's previous history of interests but also recommend social elements which are trending among similar users.Social recommender systems use a combination of social data and attributes including user's profile bio, likes, and dislikes, purchase history, reviews and other information.Since user information on various social networks might include information such as locations provided by the user, using this information and the data existing in the data base, it might actually be possible to suggest user with a much more apt recommendation.The proposed work uses skyline query algorithm which uses modified reciprocal scoring as an argument to recommend items to the users.