Yu Zheng, Lizhu Zhang, Xing Xie, and Wei-ying ma
3 November 2009
The advance of location-acquisition technologies enables people to record their location histories with spatio-temporal datasets, which imply the correlation between geographical regions. This correlation indicates the relationship between locations in the space of human behavior, and can enable many valuable services, such as sales promotion and location recommendation. In this paper, by taking into account a user’s travel experience and the sequentiality locations have been visited, we propose an approach to mine the correlation between locations from a large number of users’ location histories. We conducted a personalized location recommendation system using the location correlation, and evaluated this system with a large-scale real-world GPS dataset. As a result, our method outperforms the related work using the Pearson correlation.
In ACM SIGSPATIAL GIS 2009
Publisher Association for Computing Machinery, Inc.
Yu Zheng and Xing Xie. Learning travel recommendations from user-generated GPS traces, ACM Transaction on Intelligent Systems and Technology, Association for Computing Machinery, Inc., January 2011.
Yu Zheng and Xing Xie. Learning Location Correlation from GPS trajectories, IEEE, 25 May 2010.