SIMILARITY BASED PERSONALIZED LOCATION RECOMMENDATION SYSTEM USING HUMAN MOBILITY DIARY AND SPATIO TEMPORAL DATA
Venkata Praveen Kumar V
Research Scholar, Department of CSE, Annamalai University, Chidambaram, Tamil Nadu, India
Dr. S. Pazhanirajan
Assistant Professor, Department of CSE, FEAT, Annamalai University, Chidambaram, Tamil Nadu, India
Dr. S. Indraneel
HOD and Professor, Department of Cyber Security & IOT, St. Ann’s College of Engineering and Technology, Chirala, Andhra Pradesh, India
Realistic spatio-temporal trajectories for human mobility are being generated and are used in various applications. This article is going to use these spatio-temporal trajectories and is going to present a framework to suggest visiting spot recommendations based on the trajectories of the similar individuals. The above framework works in 3 steps. First step involves in identification of visiting spots, second step involve in identifying the people who visited them and the third step is the recommendation of the visiting spots to the unvisited individuals. The proposed method adds more fields to the Mobility Diary proposed by Luca Pappalardo and provide an algorithm to identify the Visiting spots. Basing on the available historical data of the individuals, we identify the people who can be suggested with above recommendations. If the individual comes in the above category and if he/she has not visited then he will be suggested with the above recommendation. We compared the proposed method with real data and found that the method is generating results in more accurate way.
Keywords: Spatio Temporal Data, Location Recommendation, Point of Interest (POI), Data Mining, Human Mobility.