Conference Proceedings
Reverse k nearest neighbor search over trajectories (extended Abstract)
S Wang, Z Bao, J Shane Culpepper, T Sellis, G Cong
Proceedings IEEE 34th International Conference on Data Engineering Icde 2018 | IEEE | Published : 2018
Abstract
We study a new kind of query-a Reverse k Nearest Neighbor Search over Trajectories (RkNNT), which can be used for route planning and capacity estimation in the transportation field. Given a set of existing routes DR, a set of passenger transitions DT, and a query route Q, an RkNNT query returns all transitions that take Q as one of its k nearest travel routes. We develop an index to handle dynamic trajectory updates, so that the most up-To-date transition data is available for answering an RkNNT query using a filter-refine processing framework. Further, an application of using RkNNT to plan the optimal route in bus networks, namely MaxRkNNT, is proposed and studied. Experiments on real datas..
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Awarded by Appalachian Regional Commission
Funding Acknowledgements
This work was partially supported by ARC DP170102726, DP170102231, DP180102050, and National Natural Science Foundation of China (NSFC) 61728204, 91646204. Zhifeng Bao is supported by a Google Faculty Award.