{Reference Type}: Journal Article {Title}: Location Prediction on Trajectory Data: A Review {Author}: Wu, Ruizhi; Luo, Guangchun; Shao, Junming; Tian, Ling; Chengzong, Peng {Journal}: Big Data Mining and Analytics {ISBN/ISSN}: 2096-0654 {Year}: 2018 {Volume}: 1 {Issue}: 2 {Pages}: 108-127 {DOI}: 10.26599/BDMA.2018.9020010 {Keywords}: data mining {Keywords}: location prediction {Keywords}: trajectory data {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. {URL}: https://www.sciopen.com/article/10.26599/BDMA.2018.9020010 {Language}: en