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Boosting Moving Object Indexing through Velocity Partitioning

Summary: VP exploits skewed velocity distributions by identifying dominant velocity axes (DVAs) using PCA and k-means. Per-DVA indexes (e.g., TPR*-tree, Bx-tree) keep objects on near-1D directions, reducing search-space growth from quadratic to near-linear with speed. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10526
Venue
VLDB
Year
2012
Pagerank
4.4894309e-05
Overall Rank
8,592 | 40.23%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
7,203 Indexing Methods for Moving Object Databases: Games and Other Applications 2013 SIGMOD 4.8019323e-05
10,980 BT-Tree: A Reinforcement Learning Based Index for Big Trajectory Data 2024 SIGMOD 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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