Novel Approaches in Query Processing for Moving Object Trajectories

By D. Pfoser, Christian S. Jensen, Yannis Theodoridis. Very Large Data Bases Conference, 2000

501 citations recorded by the source corpus.

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Semantic (Web) Technology In Action: Ontology Driven Information Systems for Search, Integration and Analysis (2003, methodology): “TB-tree [28]: The Trajectory-bundle tree (TB-tree) is an R-tree-like structure that strictly preserves trajectories.”
Robust and fast similarity search for moving object trajectories (2005, background): “This separates similaritybased retrieval from queries in spatio-temporal databases where time components of trajectories are important to answer time slice or time interval queries [28].”
Discovering popular routes from trajectories (2011, background): “Other related work includes path planning by considering traffic uncertainty [17], searching similar trajectories [18], [19], [20], [21], [22], shortest path [6], [23], shortest path on time-dependent networks [24], finding the fastest path by speed patterns [25], etc.”
Querying imprecise data in moving object environments (2003, background): “A spatial index for trajectories has been developed in [14, 15].”
Indexing Large Trajectory Data Sets With SETI (2003, methodology): “In this section we present the experimental results evaluating the behavior of SETI and two other trajectory indexing structures: the 3D R*-tree and the TB-tree [21].”
Mining, indexing, and querying historical spatiotemporal data (2004, methodology): “[10] proposes 3D variants of this access method, suitable for indexing historical spatiotemporal data.”