This paper proposes Improved Spatial Social union (I-SSU), associate degree approach of similarity measuring between 2 users that integrate the interconnection among users, things locations, and time and age bracket. The improved-SSU aware location-sensitive recommendation algorithmic rule is then devised. This paper evaluates and compares the planned approach with the prevailing rating prediction and item recommendation algorithms for user age and session primarily based model. The results show that the improved-SSU-aware recommendation algorithmic rule is more practical in recommending things with the higher thought of user?s preference location, session and age bracket communication model.