Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/36717

TitleGeo-spatial analytics using the dynamic ST-SNN Approach
Author(s)Santos, Maribel Yasmina
Pires, João Moura
Moreira, Guilherme
Oliveira, Ricardo
Mendes, Fernando
Costa, Carlos
KeywordsSpatial Data
Spatio-Temporal Clustering
SNN
Density-based Clustering
Spatio-Temporal Data
Clustering
Issue dateJul-2015
PublisherIAENG
JournalLecture Notes in Engineering and Computer Science
CitationSantos, Maribel Yasmina, Joao Moura Pires, Guilherme Moreira, Ricardo Oliveira, Fernando Mendes, and Carlos Costa, “Geo-Spatial Analytics using the Dynamic ST-SNN Approach”, Proceedings of the 2015 International Conference of Data Mining and Knowledge Engineering, World Congress of Engineering, Vol. I, July 1-3, London, UK, pp. 285-290, ISBN 978-988-19253-4-3.
Abstract(s)Spatio-temporal clustering is a subfield of data mining that is increasingly gaining more scientific attention due to the advances of location-based devices that register position, time and, in some cases, other attributes. Spatio-temporal clustering intends to group objects based in their spatial and temporal similarity helping to discover interesting spatio-temporal patterns and correlations in large data sets. One of the main challenges of this area is the ability to integrate spatial, temporal and other numerical or classification information in a general-purpose approach as well as the capability to integrate, in the previously obtained clusters, newly available data. This paper presents the Dynamic ST-SNN approach in which the user has the possibility to simultaneously analyse several dimensions and incrementally add new-collected data to the existing clusters providing updated clusters.
TypeConference paper
URIhttp://hdl.handle.net/1822/36717
ISBN978-988-19253-4-3
ISSN2078-0958
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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