TY - GEN
T1 - A neural-network-based geographic tendency visualization
AU - Hotta, Hajime
AU - Hagiwara, Masafumi
PY - 2008/12/1
Y1 - 2008/12/1
N2 - In this paper, we propose a neural-network-based visualization system of geographic tendency. In general, there are some needs of understanding statistical data of geographic tendency, such as geographic marketing data, real-estate prices, and so on. The main purpose of the proposal is to visualize the tendency of these data online with interactive mapping systems, such as Google Maps. The proposed system generates translucent images of a heatmap, which shows the geographic tendency like thermograph. It consists of two steps: (I) construction of a tendency model with a neural network, (2) determine the color scale for the output heatmap. As for (I), a general regression neural network (GRNN) is employed to compose a tendency model by function approximation. As for (2), the output color scale is optimized and the heatmap is finally generated using the composed tendency model.
AB - In this paper, we propose a neural-network-based visualization system of geographic tendency. In general, there are some needs of understanding statistical data of geographic tendency, such as geographic marketing data, real-estate prices, and so on. The main purpose of the proposal is to visualize the tendency of these data online with interactive mapping systems, such as Google Maps. The proposed system generates translucent images of a heatmap, which shows the geographic tendency like thermograph. It consists of two steps: (I) construction of a tendency model with a neural network, (2) determine the color scale for the output heatmap. As for (I), a general regression neural network (GRNN) is employed to compose a tendency model by function approximation. As for (2), the output color scale is optimized and the heatmap is finally generated using the composed tendency model.
UR - http://www.scopus.com/inward/record.url?scp=62949220239&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=62949220239&partnerID=8YFLogxK
U2 - 10.1109/WIIAT.2008.141
DO - 10.1109/WIIAT.2008.141
M3 - Conference contribution
AN - SCOPUS:62949220239
SN - 9780769534961
T3 - Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
SP - 817
EP - 823
BT - Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
T2 - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
Y2 - 9 December 2008 through 12 December 2008
ER -