Spatio-temporal clustering: Neighbourhoods based on median seasonal entropy

Entropy-based Consensus for Distributed Data Clustering

The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...

Spatio-Temporal Clustering: a Survey

Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. It is relatively new subfield 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 object...

Spatio-temporal clustering methods classification

Nowadays, a vast amount of spatio-temporal data are being generated by devices like cell phones, GPS and remote sensing devices and therefore discovering interesting patterns in such data became an interesting topics for researchers. One of these topics has been spatio-temporal clustering which is a novel sub field of data mining and Recent researches in this area has focused on new methods and...

Towards a Spatio-temporal Form of Entropy

"Seismic-mass" density-based algorithm for spatio-temporal clustering

0957-4174/$ see front matter 2013 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2013.01.028 ⇑ Corresponding author. Address: Laboratory of Co Software Engineering, Department of Electronics, Tec tute of Crete, Romanou 3, Chania 73133, Greece. Tel.: E-mail address: [email protected] ( In this research work a new hybrid approach to spatio-temporal seismic clustering is proposed....