Speaker clustering is the task of grouping a set of speech utterances into speaker-specific classes. The basic techniques for solving this task are similar to those used for spea...
Abstract. We study a parametrized definition of gene clusters that permits control over the trade-off between increasing gene content versus conserving gene order within a cluster....
Abstract. This paper introduces a generator that creates problem instances for the Euclidean symmetric travelling salesman problem. To fit real world problems, we look at maps con...
Clustering of EST data is a method for the non-redundant representation of an organisms transcriptome. During clustering of large amounts of EST data, usually some large clusters ...
The k-means algorithm with cosine similarity, also known as the spherical k-means algorithm, is a popular method for clustering document collections. However, spherical k-means ca...