@Article{csse.2018.33.087,
AUTHOR = {Chen Yu, Qinmin Hong, Dezhong Yao, Hai Jin},
TITLE = {Tensor-Based User Trajectory Mining},
JOURNAL = {Computer Systems Science and Engineering},
VOLUME = {33},
YEAR = {2018},
NUMBER = {2},
PAGES = {87--94},
URL = {http://www.techscience.com/csse/v33n2/39960},
ISSN = {},
ABSTRACT = {The rapid expansion of GPS-embedded devices has showed the emerging new look of location-based services, enabling such offerings as travel guide
services and location-based social networks. One consequence is the accumulation of a rich supply of GPS trajectories, indicating individuals’ historical
position. Based on these data, we aim to mine the hot route by using a collaborative tensor calculation method. We present an efficient trajectory data
processing model for mining the hot route. In this paper, we rst model the individual’s trajectory log, extract sources and destinations, use map matching
to get the corresponding road segments, and nally apply the source-destination-road segments tensor in order to compute the recommended hot route. To
prove the validity and efficiency of the method, we conduct a collaborative route recommendation system, and the experimental result indicated that the
solution can recommend a route with considerable accuracy.},
DOI = {10.32604/csse.2018.33.087}
}