PPQ-Trajectory: Spatio-temporal Quantization for Querying in Large Trajectory Repositories
| Autor: | Shuang Wang, Hakan Ferhatosmanoglu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Computer science Quantization (signal processing) Autocorrelation General Engineering Codebook ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Databases (cs.DB) 02 engineering and technology QA76 Set (abstract data type) Computer Science - Databases 020204 information systems Path (graph theory) 0202 electrical engineering electronic engineering information engineering Trajectory Quadtree 020201 artificial intelligence & image processing Algorithm Computer Science::Databases Coding (social sciences) |
| ISSN: | 2150-8097 |
| Popis: | We present PPQ-trajectory, a spatio-temporal quantization based solution for querying large dynamic trajectory data. PPQ-trajectory includes a partition-wise predictive quantizer (PPQ) that generates an error-bounded codebook with autocorrelation and spatial proximity-based partitions. The codebook is indexed to run approximate and exact spatio-temporal queries over compressed trajectories. PPQ-trajectory includes a coordinate quadtree coding for the codebook with support for exact queries. An incremental temporal partition-based index is utilised to avoid full reconstruction of trajectories during queries. An extensive set of experimental results for spatio-temporal queries on real trajectory datasets is presented. PPQ-trajectory shows significant improvements over the alternatives with respect to several performance measures, including the accuracy of results when the summary is used directly to provide approximate query results, the spatial deviation with which spatio-temporal path queries can be answered when the summary is used as an index, and the time taken to construct the summary. Superior results on the quality of the summary and the compression ratio are also demonstrated. To appear at VLDB 2021 |
| Databáze: | OpenAIRE |
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