Moving Objects: Combining Gradual Rules and Spatial-Temporal Patterns - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2011

Moving Objects: Combining Gradual Rules and Spatial-Temporal Patterns

Abstract

Mining gradual patterns plays a crucial role in many real world applications where very large and complex numerical data must be handled, e.g., biological databases, survey databases, data streams or sensor readings. Gradual rules highlight complex order correlations of the form. Such rules have been studied for a long time and recently scalable algorithms have been proposed to addressthisissue. However, mining gradual patternsremainschallengingin mobileobject applications. In the other hand, mining frequent moving objects patterns is also very useful in many applications such as traffic management, mobile commerce, animals tracking. Those two techniques are very efficient to discover interesting rules and patterns; however, in some aspect, each individual technique could not help us to fully understand and discover interesting items and patterns. In this paper, we present a novel concept in that gradual pattern and spatio-temporal pattern are combined together to extract gradual-spatio-temporal rules. We also propose a novel algorithm, named GSTD, to extract such rules. Conducted experimentson a real dataset show that new kindsof patternscan be extracted.
Fichier principal
Vignette du fichier
ICSDM2011.pdf (498.45 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

lirmm-00798312 , version 1 (22-03-2019)

Identifiers

Cite

Nhat Hai Phan, Pascal Poncelet, Maguelonne Teisseire. Moving Objects: Combining Gradual Rules and Spatial-Temporal Patterns. ICSDM: International Conference on Spatial Data Mining and Geographical Knowledge Services, Jun 2011, Fuzhou, China. pp.131-136, ⟨10.1109/ICSDM.2011.5969019⟩. ⟨lirmm-00798312⟩
124 View
75 Download

Altmetric

Share

Gmail Facebook X LinkedIn More