期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2011
卷号：2
期号：4
页码：1501-1504
出版社：TechScience Publications
摘要：The main objective of the spatial data mining is to discover hidden complex knowledge from spatial and not spatial data despite of their huge amount and the complexity of spatial relationships computing. However, the spatial data mining methods are still an extension of those used in conventional data mining. Spatial data is a highly demanding field because huge amounts of spatial data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collected data far exceeded human's ability to analyze. Recent studies on data mining have extended the scope of data mining from relational and transactional databases to spatial databases. This paper summarizes recent works on spatial data mining, from spatial data generalization, to spatial data clustering, mining spatial association rules, etc. It shows that spatial data mining is a promising field, with fruitful research results and many challenging issues. The main aim of this paper shows the existing methods of clustering and association rules based on spatial data, i.e collected from large amount of spatial data basests.
关键词：spatial data mining; clustering algorithms; knowledge;discovery.hing.s.
