Sciweavers

Share
TKDE
2008

A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets

9 years 10 months ago
A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets
Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns identifies significant event-type sequences. Such spatio-temporal sequential patterns are crucial to the investigation of spatial and temporal evolutions of phenomena in many application domains. Recent research literature has explored the sequential patterns on transaction data and trajectory analysis on moving objects. However, these methods cannot be directly applied to mining sequential patterns from a large number of spatio-temporal events. Two major research challenges still remain: 1) the definition of significance measures for spatio-temporal sequential patterns to avoid spurious ones and 2) the algorithmic design under the significance measures, which may not guarantee the downward closure property. In this paper, we propose a sequence index as the significance measure for spatio-temporal sequential patte...
Yan Huang, Liqin Zhang, Pusheng Zhang
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TKDE
Authors Yan Huang, Liqin Zhang, Pusheng Zhang
Comments (0)
books