Trip Oriented Search on Activity Trajectory

Chen, Wei, Zhao, Lei, Xu, Jia-Jie, Liu, Guan-Feng, Zheng, Kai and Zhou, Xiaofang (2015) Trip Oriented Search on Activity Trajectory. Journal of Computer Science and Technology, 30 4: 745-761. doi:10.1007/s11390-015-1558-6


Author Chen, Wei
Zhao, Lei
Xu, Jia-Jie
Liu, Guan-Feng
Zheng, Kai
Zhou, Xiaofang
Title Trip Oriented Search on Activity Trajectory
Journal name Journal of Computer Science and Technology   Check publisher's open access policy
ISSN 1000-9000
1860-4749
Publication date 2015-07-01
Year available 2015
Sub-type Article (original research)
DOI 10.1007/s11390-015-1558-6
Open Access Status Not Open Access
Volume 30
Issue 4
Start page 745
End page 761
Total pages 17
Place of publication New York, United States
Publisher Springer New York LLC
Collection year 2016
Language eng
Formatted abstract
Driven by the flourish of location-based services, trajectory search has received significant attentions in recent years. Different from existing studies that focus on searching trajectories with spatio-temporal information and text de-scriptions, we study a novel problem of searching trajectories with spatial distance, activities, and rating scores. Given a query q with a threshold of distance, a set of activities, a start point S and a destination E, trip oriented search on activity trajectory (TOSAT) returns k trajectories that can cover the activities with the highest rating scores within the threshold of distance. In addition, we extend the query with an order, i.e., order-sensitive trip oriented search on activity trajectory (OTOSAT), which takes both the order of activities in a query q and the order of trajectories into consideration. It is very challenging to answer TOSAT and OTOSAT efficiently due to the structural complexity of trajectory data with rating information. In order to tackle the problem efficiently, we develop a hybrid index AC-tree to organize trajectories. Moreover, the optimized variant RAC+-tree and novel algorithms are introduced with the goal of achieving higher performance. Extensive experiments based on real trajectory datasets demonstrate that the proposed index structures and algorithms are capable of achieving high efficiency and scalability.
Keyword trajectory search
rating score
activity trajectory
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Information Technology and Electrical Engineering Publications
 
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