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The discovery of hidden and valuable periodic patterns could reveal valuable information to the data analyst. Periodic patterns extracted from spatio-temporal trajectories of moving objects unveil regular movement behavior. This paper surveys the breath and depth review of spatio-temporal periodic pattern mining and presents an overview of periodic pattern discovering methods from spatio-temporal...
Due to the ubiquity of GPS enabled devices and the advances in sensing technologies, trajectory data has become abundant. Regions of interest are important since they describe specific hot-spots within the data that often correlate with domain specific phenomena. Traditional region of interest mining utilises grid based rasters to model space. This suffers from two main problems: hard to determine...
Higher order information includes k-nearestneighbor information and k-order region information that are of great importance when the first order or lower order information is not functioning. Despite of the importance of direction in spatio-temporal analysis, directional higher order information has received almost no attention. This paper introduces a new directional higher order information dissimilarity...
Flickr represents a massive opportunity to mine valuable human movement data from geo-tagged photos. However, existing Flickr trajectory data mining research has not considered mining frequent trajectory patterns whilst also considering the temporal domain. Therefore, a significant opportunity exists to demonstrate the application of a pattern mining algorithm to a large geo-tagged photo dataset....
The Internet has penetrated to every aspect of our daily life. Users are feeding their georeferenced knowledge, preference, consumer patterns and behaviors, likes and dislikes, and living patterns to the Web. Proper understanding of these user-provided georeferenced Web data is of great importance. This article combines Web 2.0 and Geospatial Web to retrieve and map user-driven data, and mixes clustering...
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