Remote sensing and mobile devices nowadays collect a huge amount of spatial data which have to be analysed in order to discover interesting knowledge about economical, social and scientific problems. However, the presence of a spatial dimension adds some problems to data mining tasks. The geometrical representation and relative positioning of spatial objects implicitly define spatial relationsh...

Many organizations rely on spatial analysis to make business and agency decisions and to conduct research. The main difference between data mining in relational DBS and in spatial DBS is the interest of neighboring object’s attributes may have an influence on the current object, so the neighboring object have to be considered as well. The explicit location and extension of spatial objects defin...

Mining knowledge from large amounts of spatial data is known as spatial data mining. It becomes a highly demanding field because huge amounts of spatial data have been collected in various applications ranging from geo-spatial data to bio-medical knowledge. The amount of spatial data being collected is increasing exponentially. So, it far exceeded human’s ability to analyze. Recently, clusterin...

Remote sensing and mobile devices nowadays collect a huge amount of spatial data, which have to be analysed in order to discover interesting information about economic, social and scientific problems. However, the presence of a spatial dimension adds some problems to data mining tasks. The geometrical representation and relative positioning of spatial objects implicitly define spatial relations...

We address the problem of identifying color variation in color skin lesion color. We adapt a spatial data mining method to this task and integrate with a segmentation method to identify significant color regions in an image. The resulting regions are compared with human perception via Kappa statistical test. Evaluation of the results indicate that the method approximates human judgment well and...

health databases contain a wide scope of clinical data to explore relationships and patterns that can lead to new medical knowledge.today, the emergence of integrated information systems and growth of information technologies have better highlighted the importance of such databases. data mining is among the technological advances toward data management whose integration with traditional methods...