Compact Representations of Event Sequences
| UDC.coleccion | Investigación | es_ES |
| UDC.conferenceTitle | 2018 Data Compression Conference (DCC 2018) | es_ES |
| UDC.departamento | Ciencias da Computación e Tecnoloxías da Información | es_ES |
| UDC.endPage | 246 | es_ES |
| UDC.grupoInv | Laboratorio de Bases de Datos (LBD) | es_ES |
| UDC.startPage | 237 | es_ES |
| dc.contributor.author | Brisaboa, Nieves R. | |
| dc.contributor.author | Bernardo, Guillermo de | |
| dc.contributor.author | Navarro, Gonzalo | |
| dc.contributor.author | Seco, Diego | |
| dc.contributor.author | Varela Rodeiro, Tirso | |
| dc.date.accessioned | 2024-11-19T13:12:09Z | |
| dc.date.available | 2024-11-19T13:12:09Z | |
| dc.date.issued | 2018-03 | |
| dc.description | The congress was held in Snowbird, Utah, USA. 27-30 March 2018 | es_ES |
| dc.description.abstract | [Abstract]: We introduce a new technique for the efficient management of large sequences of multi-dimensional data, which takes advantage of regularities that arise in real-world datasets and supports different types of aggregation queries. More importantly, our representation is flexible in the sense that the relevant dimensions and queries may be used to guide the construction process, easily providing a space-time tradeoff depending on the relevant queries in the domain. We provide two alternative representations for sequences of multidimensional data and describe the techniques to efficiently store the datasets and to perform aggregation queries over the compressed representation. We perform experimental evaluation on realistic datasets, showing the space efficiency and query capabilities of our proposal. | es_ES |
| dc.description.sponsorship | Funded in part by European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 690941. NB, GdB and TR supported by: CDTI, MINECO grant ITC-20151247; MINECO grants TIN2016-78011-C4-1-R, TIN2016-77158-C4-3-R and TIN2013-46238-C4-3-R; and Xunta de Galicia grant ED431C 2017/58 GRC. DS supported by: MINECO (PGE and FEDER) grants TIN2016-77158-C4-3-R and TIN2013-46801-C4-3-R, and Fondecyt-Conicyt grant number 1170497. GN supported by Basal Funds FB0001, Conicyt, Chile. | es_ES |
| dc.description.sponsorship | Xunta de Galicia; ED431C 2017/58 GRC | es_ES |
| dc.description.sponsorship | Chile. Comisión Nacional de Investigación Científica y Tecnológica; 1170497 | es_ES |
| dc.identifier.citation | N. R. Brisaboa, G. De Bernardo, G. Navarro, T. V. Rodeiro, y D. Seco, «Compact Representations of Event Sequences», en 2018 Data Compression Conference, Snowbird, UT: IEEE, mar. 2018, pp. 237-246. doi: 10.1109/DCC.2018.00032. | es_ES |
| dc.identifier.issn | 2375-0359 | |
| dc.identifier.uri | http://hdl.handle.net/2183/40182 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | IEEE | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/690941 | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ITC-20151247/ES/GIRO: GENERACIÓN, GESTIÓN E INTEGRACIÓN DE RUTAS EN OLAP | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2016-78011-C4-1-R/ES/DATOS 4.0: RETOS Y SOLUCIONES | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2016-77158-C4-3-R/ES/VELOCITY: PROCESADO EFICIENTE DE BIG DATA ESPAZO-TEMPORAL PARA FLATCITY | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2013-46238-C4-3-R/ES/4V: VOLUMEN, VELOCIDAD, VARIEDAD Y VALIDEZ EN LA GESTIÓN INNOVADORA DE DATOS: UDC | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2013-46801-C4-3-R/ES/HERMES-SPACE&TIME-HEALTHY AND EFFICIENT ROUTES IN MASSIVE OPEN-DATA BASED SMART CITIES: SPATIO-TEMPORAL MODELING AND QUERYING | es_ES |
| dc.relation.uri | https://doi.org/10.1109/DCC.2018.00032 | es_ES |
| dc.rights | Copyright © 2018, IEEE | es_ES |
| dc.rights.accessRights | open access | es_ES |
| dc.subject | Proposals | es_ES |
| dc.subject | Data structures | es_ES |
| dc.subject | Data warehouses | es_ES |
| dc.subject | Roads | es_ES |
| dc.subject | Databases | es_ES |
| dc.subject | Geographic information systems | es_ES |
| dc.subject | Aggregates | es_ES |
| dc.title | Compact Representations of Event Sequences | es_ES |
| dc.type | conference output | es_ES |
| dspace.entity.type | Publication | |
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| relation.isAuthorOfPublication | ba377c82-883d-4ed6-8700-a3d45ff9af17 | |
| relation.isAuthorOfPublication.latestForDiscovery | 42f2c226-9868-4516-8efd-2cd3c6692034 |
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