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dc.contributor.authorBrisaboa, Nieves R.
dc.contributor.authorFariña, Antonio
dc.contributor.authorGalaktionov, Daniil
dc.contributor.authorRodríguez, M. Andrea
dc.date.accessioned2017-02-23T19:23:15Z
dc.date.available2017-02-23T19:23:15Z
dc.date.issued2016-09-21
dc.identifier.citationBrisaboa N.R., Fariña A., Galaktionov D., Rodríguez M.A. (2016) Compact Trip Representation over Networks. In: Inenaga S., Sadakane K., Sakai T. (eds) String Processing and Information Retrieval. SPIRE 2016. Lecture Notes in Computer Science, vol 9954. Springer, Chames_ES
dc.identifier.issn1611-3349
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/2183/18178
dc.descriptionThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46049-9_23es_ES
dc.description.abstract[Abstract] We present a new Compact Trip Representation ( CTRCTR ) that allows us to manage users’ trips (moving objects) over networks. These could be public transportation networks (buses, subway, trains, and so on) where nodes are stations or stops, or road networks where nodes are intersections. CTRCTR represents the sequences of nodes and time instants in users’ trips. The spatial component is handled with a data structure based on the well-known Compressed Suffix Array ( CSACSA ), which provides both a compact representation and interesting indexing capabilities. We also represent the temporal component of the trips, that is, the time instants when users visit nodes in their trips. We create a sequence with these time instants, which are then self-indexed with a balanced Wavelet Matrix ( WMWM ). This gives us the ability to solve range-interval queries efficiently. We show how CTRCTR can solve relevant spatial and spatio-temporal queries over large sets of trajectories. Finally, we also provide experimental results to show the space requirements and query efficiency of CTRCTR .es_ES
dc.description.sponsorshipMinisterio de Economía y Competitividad; TIN2013-46238-C4-3-Res_ES
dc.description.sponsorshipMinisterio de Economía y Competitividad; TIN2013-47090-C3-3-Pes_ES
dc.description.sponsorshipMinisterio de Economía y Competitividad; IDI-20141259es_ES
dc.description.sponsorshipMinisterio de Economía y Competitividad; ITC-20151305es_ES
dc.description.sponsorshipMinisterio de Economía y Competitividad; ITC-20151247es_ES
dc.description.sponsorshipXunta de Galicia; GRC2013/053es_ES
dc.description.sponsorshipChile.Fondo Nacional de Desarrollo Científico y Tecnológico; 1140428es_ES
dc.description.sponsorshipChile. Instituto de Sistemas Complejos de Ingeniería ; FBO 16es_ES
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/690941
dc.relation.urihttp://link.springer.com/chapter/10.1007%2F978-3-319-46049-9_23es_ES
dc.subjectCompact Trip Representationes_ES
dc.subjectWavelet Matrixes_ES
dc.titleCompact Trip Representation over Networkses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleLecture Notes in Computer Sciencees_ES
UDC.volume9954es_ES
UDC.startPage240es_ES
UDC.endPage253es_ES
dc.identifier.doi10.1007/978-3-319-46049-9_23
UDC.conferenceTitle23rd International Symposium, SPIRE 2016, Beppu, Japan, October 18-20, 2016es_ES


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