: The issue of determining "the right number of clusters" in K-Means has attracted considerable interest, especially in the recent years. Cluster intermix appears to be a...
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
Annotation of protein function often arises in the context of partially complete genomes but is not adequately addressed. We present an annotation method by extracting ortholog cl...
Akshay Vashist, Casimir A. Kulikowski, Ilya B. Muc...
: This work focuses on clustering a site into groups of documents that are predictive of future user accesses. Two approaches have been developed and tested. The first approach use...
This paper introduces an additive fuzzy clustering model for similarity data as oriented towards representation and visualization of activities of research organizations in a hiera...