doi: 10.7763/IJMLC.2012.V2.121
Data Mining in GIS: A Novel Context-Based Fuzzy Geographically Weighted Clustering Algorithm
Le Hoang Son1
,
Pier Luca Lanzi2 ,
Bui Cong Cuong3 ,
- 1Center for High Performance Computing, VNU University of Science, Vietnam.
- 2Department of Electronics and Information, Politecnico di Milano, Milan, Italy.
- 3Institute of Mathematics, Vietnamese Academy of Science, Vietnam.
Abstract
Geographic Information Systems (GIS) play a very important role to researches and industries. In fact, there have been some studies related to the development of this kind of systems as well as methods of mining attribute GIS data. In this paper, we will explore an aspect of Data Mining in GIS, that is, GIS Clustering for Geo-Demographic Analysis and present a novel context-based fuzzy geographically weighted clustering algorithm to solve such task.
Keywords
- Clustering
- data mining
- GIS
- Geo-Demographic analysis
How to Cite
Le Hoang Son, Pier Luca Lanzi, Bui Cong Cuong, and Hoang Anh Hung, "Data Mining in GIS: A Novel Context-Based Fuzzy Geographically Weighted Clustering Algorithm," International Journal of Machine Learning, vol. 2, no. 3, pp. 235-238, 2012. https://doi.org/10.7763/IJMLC.2012.V2.121
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).