Personalized Location Recommendation System based on Spatio Temporal Data and Human Mobility Diary
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 frame work to suggest visiting spot recommendations based on the trajectories of the similar individuals. The above frame work 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.