Paper Title
Personalized Recommendations Using Apriori Algorithm For Frequent Data Set Mining

Abstract
Abstract—The paper presents an overview of the field of current recommender systems and presents a new system based on the users locations along with the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches. The paper also describes various limitations of current recommendation methods and discusses how the new presented recommendation system overcomes the same. This recommendation system uses the check in data from the users’ check-in history to analyze the behavioral patterns of the users’ checkins, using the algorithms – Apriori at the base and Location prediction based on favorites and personal history over it.