Two-level indexes have been widely used to handle trajectories of moving objects that are constrained to a network. The top-level of these indexes handles the spatial dimension, whereas the bottom level handles the temporal dimension. The latter turns out to be an instance of the interval-intersection problem, but it has been tackled by non-specialized spatial indexes. In this work, we propose the use of a compact data structure on the bottom level of these indexes. Our experimental evaluation shows that our approach is both faster and smaller than existing solutions.
CITATION STYLE
Rivera, R., Rodríguez, M. A., & Seco, D. (2018). Faster and smaller two-level index for network-based trajectories. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11147 LNCS, pp. 348–362). Springer Verlag. https://doi.org/10.1007/978-3-030-00479-8_28
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