Spatio-temporal SNN: Integrating Time and Space in the Clustering Process,

Maribel Yasmina Santos (superv.), Universidade do Minho, December 2013.

Abstract:Spatio-temporal clustering is a new subfield of data mining that is increasingly gaining scientific attention due to the technical advances of location-based or environmental devices that register position, time and, in some cases, other semantic attributes. One of the main challenges of this area is to integrate several dimensions in the clustering process with a general-purpose approach.
This work intends to implement in the SNN clustering algorithm the ability to deal with spatio-temporal data allowing the integration of space, time and one or more semantic attributes in the clustering process, the 4D+SNN approach.
The results presented in this work are very promising as the approach proposed is able to identify interesting patterns on spatio-temporal data. Concretely, it can identify clusters taking into account simultaneously the spatial and temporal dimension and it also has good results when adding one or more semantic attributes.