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dc.date.accessioned 2015-12-14T12:49:44Z
dc.date.available 2015-12-14T12:49:44Z
dc.date.issued 2015-11
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/50180
dc.description.abstract The classic use of Stream Processing platforms enables working with data in real time, which allows you to generate data analysis quickly attending to a decisionmaking process. However, you can use these platforms for other applications such as indexing and subsequent use of similarity search objects in a database. The images can be displayed on a metric space, which has features that allow rules to discard a not similar image quickly without making costly computations. This paper presents the use of a Stream Processing platform to index images generated by different users. For this, it is necessary to represent these images by vectors containing different MPGE-7 features. This paper shows a Stream Processing platform using its processing elements (PEs) in parallel to speed up the operations involved in the index construction. en
dc.format.extent 93-99 es
dc.language en es
dc.subject stream processing en
dc.subject Metrics es
dc.subject metrics spaces en
dc.subject MPEG-7 en
dc.subject sparse spatial selection en
dc.title Stream processing to solve image search by similarity en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST41-Paper-8.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Lobos, Jair es
sedici.creator.person Gil Costa, Graciela Verónica es
sedici.creator.person Reyes, Nora Susana es
sedici.creator.person Printista, Alicia Marcela es
sedici.creator.person Marín, Mauricio es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution 3.0 Unported (CC BY 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by/3.0/
sedici.description.peerReview peer-review es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 15, no. 2 es


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Creative Commons Attribution 3.0 Unported (CC BY 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution 3.0 Unported (CC BY 3.0)