Geo-Spatial Analytics using the Dynamic ST-SNN Approach

Maribel Yasmina Santos, Joao Moura Pires, Guilherme Moreira, Ricardo Oliveira, Fernando Mendes, Carlos Costa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationWORLD CONGRESS ON ENGINEERING, WCE 2015, VOL I
EditorsSI Ao, L Gelman, DWL Hukins, A Hunter, AM Korsunsky
PublisherINT ASSOC ENGINEERS-IAENG
Pages285-290
Number of pages6
ISBN (Print)978-988-19253-4-3
Publication statusPublished - 2015
EventWorld Congress on Engineering (WCE 2015) - London
Duration: 1 Jul 20153 Jul 2015

Publication series

NameLecture Notes in Engineering and Computer Science
PublisherINT ASSOC ENGINEERS-IAENG
ISSN (Print)2078-0958

Conference

ConferenceWorld Congress on Engineering (WCE 2015)
CityLondon
Period1/07/153/07/15

Keywords

  • Spatial Data
  • Spatio-Temporal Data
  • Clustering
  • Density-based Clustering
  • SNN
  • DIFFERENT SIZES
  • DENSITIES
  • ALGORITHM
  • CLUSTERS
  • SHAPES

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