The problem of finding an optimal bipartition of a rectangle set has a direct impact on query performance of dynamic R-trees. During update operations, overflowed nodes need to be...
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
The use of genotypic populations is necessary for adaptation in Evolutionary Algorithms. We use a technique called form-invariant commutation to study the immediate effect of evol...
In this paper, we present a general data clustering algorithm which is based on the asymmetric pairwise measure of Markov random walk hitting time on directed graphs. Unlike tradi...
Abstract. Data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. In many areas, complex dista...
Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfei...