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General Information
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2012 Vol.2(3): 235-238 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.121

Data Mining in GIS: A Novel Context-Based Fuzzy Geographically Weighted Clustering Algorithm

Le Hoang Son, Pier Luca Lanzi, Bui Cong Cuong, and Hoang Anh Hung

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.

Index Terms—Clustering, data mining, GIS,Geo-Demographic analysis.

Le Hoang Son and Hoang Anh Hung are with the Center for High Performance Computing, VNU University of Science, Vietnam (e-mail: sonlh@vnu.edu.vn).
Pier Luca Lanzi is with the Department of Electronics and Information, Politecnico di Milano, Milan, Italy (e-mail: lanzi@elet.polimi.it).
Bui Cong Cuong is with the Institute of Mathematics, Vietnamese Academy of Science, Vietnam (e-mail: ccuong@inbox.com).

[PDF]

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 and Computing vol. 2, no. 3, pp. 235-238, 2012.

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