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Faster compressed quadtrees
dc.contributor.author | Bernardo, Guillermo de | |
dc.contributor.author | Gagie, Travis | |
dc.contributor.author | Ladra, Susana | |
dc.contributor.author | Navarro, Gonzalo | |
dc.contributor.author | Seco, Diego | |
dc.date.accessioned | 2024-07-09T12:23:36Z | |
dc.date.issued | 2023-02 | |
dc.identifier.citation | G. de Bernardo, T. Gagie, S. Ladra, G. Navarro, and D. Seco, "Faster compressed quadtrees", Journal of Computer and System Sciences, Vol. 131, pp. 86 - 104, Feb. 2023, doi: 10.1016/j.jcss.2022.09.001 | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/37832 | |
dc.description | ©2023 Elsevier B.V. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/byncnd/ 4.0/. This version of the article has been accepted for publication in Future Generation Computer Systems. The Version of Record is available online at https:// doi.org/10.1016/j.jcss.2022.09.001 | es_ES |
dc.description | Versión aceptada | es_ES |
dc.description | An early partial version of this paper appeared in Proc. of the Data Compression Conference 2015. | es_ES |
dc.description.abstract | [Abstract]: Real-world point sets tend to be clustered, so using a machine word for each point is wasteful. In this paper we first show how a compact representation of quadtrees using O(1) bits per node can break this bound on clustered point sets, while offering efficient range searches. We then describe a new compact quadtree representation based on heavy-path decompositions, which supports queries faster than previous compact structures. We present experimental evidence showing that our structure is competitive in practice. | es_ES |
dc.description.sponsorship | Partially funded by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 690941. GdB and SL funded by MCIN/AEI/10.13039/501100011033 [grants PID2020-114635RB-I00 (EXTRACompact), PID2019-105221RB-C41 (MAGIST)], by MCIN/AEI/10.13039/501100011033, “NextGenerationEU/PRTR” [grants PDC2021-120917-C21 (SIGTRANS) , PDC2021-121239-C31 (FLATCITY-POC)], by GAIN/Xunta de Galicia [grant ED431C 2017/53 (GRC) ], and also supported by the Centro de Investigación de Galicia “CITIC”, funded by Xunta de Galicia , FEDER Galicia 2014-2020 80%, SXU 20% [grant ED431G 2019/01 (CSI) ]. TG funded by NSERC Discovery Grant RGPIN-07185-2020. GN and DS funded by ANID - Millennium Science Initiative Program - Code ICN17_002 , Chile. GN funded by FONDECYT Grant 1-200038 , Chile. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2017/53 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.description.sponsorship | Natural Sciences and Engineering Research Council of Canada; RGPIN-07185-2020 | es_ES |
dc.description.sponsorship | Chile. Agencia Nacional de Investigación y Desarrollo; ICN17_002 | es_ES |
dc.description.sponsorship | Chile. Comisión Nacional de Investigación Científica y Tecnológica; 1-200038 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier B.V. | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/690941 | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114635RB-I00/ES/EXPLOTACIÓN ENRIQUECIDA DE TRAYECTORIAS CON ESTRUCTURAS DE DATOS COMPACTAS Y GIS | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105221RB-C41/ES/VISUALIZACION Y EXPLORACION BASADA EN FLUJOS Y ANALITICA DE BIG DATA ESPACIAL/ | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PDC2021-120917-C21/ES/SIGTRANS | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PDC2021-121239-C31/ES/FLATCITY-POC | es_ES |
dc.relation.uri | https://doi.org/10.1016/j.jcss.2022.09.001 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Clustered points | es_ES |
dc.subject | Compact data structures | es_ES |
dc.subject | Heavy-path decomposition | es_ES |
dc.subject | Quadtrees | es_ES |
dc.subject | Range queries | es_ES |
dc.title | Faster compressed quadtrees | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/embargoedAccess | es_ES |
dc.date.embargoEndDate | 2025-02-01 | es_ES |
dc.date.embargoLift | 2025-02-01 | |
UDC.journalTitle | Journal of Computer and System Sciences | es_ES |
UDC.volume | 131 | es_ES |
UDC.startPage | 86 | es_ES |
UDC.endPage | 104 | es_ES |
dc.identifier.doi | 10.1016/j.jcss.2022.09.001 |
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