A Kind of Improved VGI Spatial Association Rule Mining Algorithm Based on Multi-level Semantic Constraints

Lingli Zhao, Shuai Liu, Junsheng Li, Hongwei Guo

Abstract


VGI information is a kind of multi-source data absolutely, which contains spatial data and tagging data. VGI data have multi-level semantic. Spatial data mining is a demanding field since huge amounts of spatial data have been collected in various applications, ranging from remote sensing to geographical information systems, VGI data, computer cartography, environmental assessment and planning. The paper proposes a kind of VGI spatial association rule mining, which can extract frequent set quickly from VGI data. The experiment shows that the proposed algorithm is valid and efficient.


DOI
10.12783/dtcse/iceiti2016/6135

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