We introduce a class of graphs called an intersecting clustered graph that is a clustered graph with intersections among clusters. We propose a novel method for nicely drawing the...
We study methods to initialize or bias different clustering methods using prior information about the "importance" of a keyword w.r.t. the whole document collection or a...
We present a coherent framework for data clustering. Starting with a Hopfield network, we show the solutions for several well-motivated clustering objective functions are principa...
Abstract. Resampling methods are among the best approaches to determine the number of clusters in prototype-based clustering. The core idea is that with the right choice for the nu...
In this paper, a new fuzzy clustering algorithm that uses cellular learning automata based evolutionary computing (CLA-EC) is proposed. The CLA-EC is a model obtained by combining...
Reza Rastegar, A. R. Arasteh, Arash Hariri, Mohamm...