4D(+)SNN

A Spatio-temporal Density-based Clustering Approach with 4D Similarity

Ricardo Oliveira, Maribel Yasmina Santos, Joao Moura-Pires

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 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 or environmental devices that register position, time and, in some cases, other semantic attributes. This process pretends to group objects based in their spatial and temporal similarity helping to discover interesting patterns and correlations in large data sets. One of the main challenges of this area is the ability to integrate several dimensions in a general-purpose approach. In this paper, such general approach is proposed, based on an extension of the SNN (Shared Nearest Neighbor) algorithm. The 4D(+)SNN algorithm allows the integration of space, time and one or more semantic attributes in the clustering process. This algorithm is able to deal with different data sets and different discovery purposes as the user has the ability to weight the importance of each dimension in the discovery process. The results obtained are very promising as show interesting findings on data and open the possibility of integration of several dimensions of analysis in the clustering process.

Original languageEnglish
Title of host publication2013 IEEE 13TH INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW)
EditorsW Ding, T Washio, H Xiong, G Karypis, B Thuraisingham, D Cook, Wu
PublisherIEEE
Pages1045-1052
Number of pages8
DOIs
Publication statusPublished - 2013
EventIEEE 13th International Conference on Data Mining (ICDM) - Dallas
Duration: 7 Dec 201310 Dec 2013

Publication series

NameIEEE International Conference on Data Mining
PublisherIEEE
ISSN (Print)1550-4786

Conference

ConferenceIEEE 13th International Conference on Data Mining (ICDM)
CityDallas
Period7/12/1310/12/13

Keywords

  • clustering
  • density-based clustering
  • spatio-temporal data
  • distance function
  • spatio-temporal clustering

Cite this

Oliveira, R., Santos, M. Y., & Moura-Pires, J. (2013). 4D(+)SNN: A Spatio-temporal Density-based Clustering Approach with 4D Similarity. In W. Ding, T. Washio, H. Xiong, G. Karypis, B. Thuraisingham, D. Cook, & Wu (Eds.), 2013 IEEE 13TH INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW) (pp. 1045-1052). (IEEE International Conference on Data Mining). IEEE. https://doi.org/10.1109/ICDMW.2013.119