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Proceedings Paper

Mapping the knowledge of spatial data mining
Author(s): Zuocheng Wang; Lixia Xue; Yongshu Li; Linlin Wang
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Paper Abstract

Map is the model of spatial data. It is the basis of spatial database. Because of the complexity of spatial data mining and the diversity of spatial relations, too many spatial rules have been discovered in spatial data mining. In order to comprehending the knowledge contained in spatial rules, spatial data mining visualization has attracted a great deal of attention. In fact, map is not only one of the objects of spatial data mining, but also one of the predominant visualization tools of spatial rules or knowledge. This paper proposes that map is the proper visual method of spatial rules from spatial data mining. By the visual variables of map expressing, such as static variables, including shape, size, color, brightness, design, texture and dynamic variables, including video, sound, and so on, Map can visualize static and dynamic knowledge. From the point of view of map expressing, spatial knowledge or rules can be classified four categories, spatial characteristic rules, spatial distribution rules, spatial relation rules and temporal-spatial evolution rules. We propose visualization models and methods for each category by virtue of the visual variables of map expressing. Along with the development of 3D map, map can visualize spatial knowledge better and facilitate comprehending the spatial rules from spatial data mining.

Paper Details

Date Published: 2 December 2005
PDF: 6 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 604510 (2 December 2005); doi: 10.1117/12.650708
Show Author Affiliations
Zuocheng Wang, Southwest Jiaotong Univ. (China)
Chongqing Univ. of Posts and Telecommunications (China)
Lixia Xue, Southwest Jiaotong Univ. (China)
Chongqing Univ. of Posts and Telecommunications (China)
Yongshu Li, Southwest Jiaotong Univ. (China)
Linlin Wang, Chongqing Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 6045:
MIPPR 2005: Geospatial Information, Data Mining, and Applications
Jianya Gong; Qing Zhu; Yaolin Liu; Shuliang Wang, Editor(s)

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