PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Kisilevich S., Mansmann F., Nanni M., Rinzivillo S. Spatio-temporal clustering: a survey. Technical report, 2010.
 
 
Abstract
(English)
Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. It is relatively new sub-field of data mining which gained high popularity especially in geographic information sciences due to the pervasiveness of all kinds of location-based or environmental devices that record position, time or/and environmental properties of an object or set of objects in real-time. As a consequence, different types and large amounts of spatio-temporal data became available that introduce new challenges to data analysis and require novel approaches to knowledge discovery. In this chapter we concentrate on the spatio-temporal clustering in geographic space. First, we provide a classification of different types of spatio-temporal data. Then, we focus on one type of spatio-temporal clustering - trajectory clustering, provide an overview of the state-of-the-art approaches and methods of spatio-temporal clustering and finally present several scenarios in different application domains such as movement, cellular networks and environmental studies.
URL: http://kdd.isti.cnr.it/~nanni/papers/DMKD_Handbook_STClustering_submitted.pdf
Subject Spatio-temporal clustering
Trajectory clustering
I.5.3 Clustering
62-07 Data analysis


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