Geo-Spatial Analytics using the DynamicST-SNN Approach

Posted onAuthorRicardo Silva

Maribel Yasmina Santos, João Moura Pires, Guilherme Moreira, Ricardo Oliveira, Fernando Mendes, Carlos Costa: Geo-Spatial Analytics using the DynamicST-SNN Approach. In: IAENG, 2015, ISBN: 978-988-19253-4-3.

Abstract

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.

Links

    BibTeX (Download)

    @incollection{Silva_2015,
title = {Geo-Spatial Analytics using the DynamicST-SNN Approach},
author = { Maribel Yasmina Santos and João Moura Pires and Guilherme Moreira and Ricardo Oliveira and Fernando Mendes and Carlos Costa},
isbn = {978-988-19253-4-3},
year  = {2015},
date = {2015-01-01},
publisher = {IAENG},
abstract = {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. },
keywords = {Clustering, Density-based Clustering, Spatial data, Spatio-temporal Data},
pubstate = {published},
tppubtype = {incollection}
}