TY - GEN
T1 - GeoSOM suite
T2 - International Conference on Computational Science and Its Applications, ICCSA 2009
AU - Henriques, Roberto
AU - Bação, Fernando
AU - Lobo, Victor
PY - 2009/11/9
Y1 - 2009/11/9
N2 - The large amount of spatial data available today demands the use of data mining tools for its analysis. One of the most used data mining techniques is clustering. Several methods for spatial clustering exist, but many consider space as just another variable. We present in this paper a tool particularly suited for spatial clustering: the GeoSOM suite. This tool implements the GeoSOM algorithm, which is based on Self-Organizing Maps. This paper describes this tool, and shows that it is adequate for exploring spatial data.
AB - The large amount of spatial data available today demands the use of data mining tools for its analysis. One of the most used data mining techniques is clustering. Several methods for spatial clustering exist, but many consider space as just another variable. We present in this paper a tool particularly suited for spatial clustering: the GeoSOM suite. This tool implements the GeoSOM algorithm, which is based on Self-Organizing Maps. This paper describes this tool, and shows that it is adequate for exploring spatial data.
KW - Exploratory spatial data analysis
KW - Self-organizing maps
KW - Spatial clustering
UR - http://www.scopus.com/inward/record.url?scp=70350634094&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-02454-2_32
DO - 10.1007/978-3-642-02454-2_32
M3 - Conference contribution
AN - SCOPUS:70350634094
SN - 364202453X
SN - 9783642024535
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 453
EP - 466
BT - Computational Science and Its Applications - ICCSA 2009 - International Conference, Proceedings
Y2 - 29 June 2009 through 2 July 2009
ER -