Leveraging cloud computing for spatial association mining
Sang Jun Park, Jin Soung Yoo · 2014
Explosive growths in geospatial data, followed by the emergence of social media and location sensing technologies, have emphasized the need to develop new and computationally efficient methods for analyzing big spatial data. Spatial association mining serves as a useful tool for discovering correlations and interesting relationships among spatial events and/or features. This paper presents an algorithmic framework that discovers spatial association patterns from large-scale spatial data on clusters of commodity machines.