Clustering is one of the most important tasks for geographic knowledge discovery. However, existing clustering methods have two severe drawbacks for this purpose. First, spatial c...
The use of Data Mining in removing current bottlenecks within Case-based Reasoning (CBR) systems is investigated along with the possible role of CBR in providing a knowledge manag...
Sarabjot S. Anand, David W. Patterson, John G. Hug...
This study investigates whether a fuzzy clustering method is of any practical value in delineating urban housing submarkets relative to clustering methods based on classic (or cri...
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...