"Location Prediction on Trajectory Data: A Review" by Ruizhi Wu, Guangchun Luo et al.

Article Title

Location Prediction on Trajectory Data: A Review

Authors

Ruizhi Wu, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Guangchun Luo, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Junming Shao, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Ling Tian, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Chengzong Peng, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

Keywords

location prediction, trajectory data, data mining

Abstract

Location prediction is the key technique in many location based services including route navigation, dining location recommendations, and traffic planning and control, to mention a few. This survey provides a comprehensive overview of location prediction, including basic definitions and concepts, algorithms, and applications. First, we introduce the types of trajectory data and related basic concepts. Then, we review existing location-prediction methods, ranging from temporal-pattern-based prediction to spatiotemporal-pattern-based prediction. We also discuss and analyze the advantages and disadvantages of these algorithms and briefly summarize current applications of location prediction in diverse fields. Finally, we identify the potential challenges and future research directions in location prediction.