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Space-efficient data structures for the inference of subsumption and disjointness relations
dc.contributor.author | Fuentes Sepúlveda, José | |
dc.contributor.author | Gatica, Diego | |
dc.contributor.author | Navarro, Gonzalo | |
dc.contributor.author | Rodríguez, M. Andrea | |
dc.contributor.author | Seco, Diego | |
dc.date.accessioned | 2024-10-03T08:59:17Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Fuentes-Sepúlveda J, Gatica D, Navarro G, Rodríguez MA, Seco D. Space-efficient datastructures for the inference of subsumption and disjointness relations. Softw: Pract Exper. 2024;1-25. doi:10.1002/spe.3367 | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/39385 | |
dc.description | The data that support the findings of this study are openly available in GBP at https://github.com/dgaticar. | es_ES |
dc.description.abstract | [Abstract]: Conventional database systems function as static data repositories, storing vast amounts of facts and offering efficient query processing capabilities. The sheer volume of data these systems store has a direct impact on their scalability, both in terms of storage space and query processing time. Deductive database systems, on the other hand, require far less storage space since they derive new knowledge by applying inference rules. The challenge is how to efficiently obtain the required derivations, compared to having them in explicit form. In this study, we concentrate on a set of predefined inference rules for subsumption and disjointness relations, including their negations. We use compact data structures to store the facts and provide algorithms to support each type of relation, minimizing even further the storage space requirements. Our experimental findings demonstrate the feasibility of this approach, which not only saves space but is often faster than a baseline that uses well-known graph traversal algorithms implemented on top of a traditional adjacency list representation to derive the relations. | es_ES |
dc.description.sponsorship | This work was funded by: ANID Millennium Science Initiative Program - Code ICN17_002; ANID Grant 77190038 and FONDECYT Grant 11220545 (1st author); PFCHA/Doctorado Nacional/2020-21201986 (2nd author); FONDECYT Grant1-230755 (3rd author); GRC: ED431C 2021/53, partially funded by GAIN/Xunta de Galicia; PID2022-141027NB-C21(EarthDL), TED2021-129245B-C21 (PLAGEMIS), PID2020-114635RB-I00 (EXTRACompact), PDC2021-121239-C31(FLATCity-POC), and PDC2021-120917-C21 (SIGTRANS): partially funded by MCIN/AEI/10.13039/501100011033 and“NextGenerationEU”/PRTR (5th author). CITIC is funded by the Xunta de Galicia through the collaboration agreementbetween the Department of Culture, Education, Vocational Training and Universities and the Galician Universities forthe reinforcement of the research centers of the Galician University System (CIGUS). | es_ES |
dc.description.sponsorship | Chile. Agencia National de Investigación y Desarrollo; ICN17_002 | es_ES |
dc.description.sponsorship | Chile. Agencia National de Investigación y Desarrollo; 77190038 | es_ES |
dc.description.sponsorship | Chile. Fondo Nacional de Desarrollo Científico y Tecnológico; 11220545 | es_ES |
dc.description.sponsorship | Chile. Fondo Nacional de Desarrollo Científico y Tecnológico; 1-230755 | es_ES |
dc.description.sponsorship | Chile. Comisión Nacional de Investigación Científica y Tecnológica; 2020-21201986 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C2021/53 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | John Wiley and Sons Ltd | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-141027NB-C21/ES/MODELADO, DESCUBRIMIENTO, EXPLORACION Y ANALISIS DE DATA LAKES MEDIOAMBIENTALES [UDC] | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/TED2021-129245B-C21/ES/PLAGEMIS | 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 2021-2023/PDC2021-121239-C31/ES/FLATCITY-POC | 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.uri | https://doi.org/10.1002/spe.3367 | es_ES |
dc.rights | © 2024 John Wiley & Sons Ltd. | es_ES |
dc.rights | This is the peer reviewed version of the following article: [Fuentes-Sepúlveda J, Gatica D, Navarro G, Rodríguez MA, Seco D. Space-efficient datastructures for the inference of subsumption and disjointness relations. Softw: Pract Exper. 2024;1-25. doi:10.1002/spe.3367 ], which has been published in final form at [https://doi.org/10.1002/spe.3367]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited. | es_ES |
dc.subject | compact data structure | es_ES |
dc.subject | deductive database system | es_ES |
dc.subject | inference rule | es_ES |
dc.subject | multigranular data model | es_ES |
dc.title | Space-efficient data structures for the inference of subsumption and disjointness relations | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/embargoedAccess | es_ES |
dc.date.embargoEndDate | 2025-10-03 | es_ES |
dc.date.embargoLift | 2025-10-03 | |
UDC.journalTitle | Software - Practice and Experience | es_ES |
dc.identifier.doi | 10.1002/spe.3367 |
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