We propose a partitioning scheme for similarity search indexes that is called Maximal Metric Margin Partitioning (MMMP). MMMP divides the data on the basis of its distribution pat...
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthe...
How can we efficiently find a clustering, i.e. a concise description of the cluster structure, of a given data set which contains an unknown number of clusters of different shape ...
The goal of the Cluster Editing problem is to make the fewest changes to the edge set of an input graph such that the resulting graph is a disjoint union of cliques. This problem i...