The automatic clustering problem of a large and complex data set into different homogeneous clusters is a challenging task. The choose of a variable length clusters centers using a good method to generate the maskers is an important phase in the evolution of a global search heuristics algorithms. In this paper, a new technique of real-coded modified differential evolution based automatic fuzzy ...

This paper presents a fully automatic speaker clustering algorithm , which consists of three components: building a distance matrix based on Gaussian models of the acoustic segments; performing hierarchical clustering on the distance matrix with the prior assumption that consecutive segments should be more likely to come from the same speaker; and selecting the best clustering solution automati...

Document clustering is the widely researched area because of large amount of rich and dynamic information are available in world wide web. It is the application of cluster analysis to texual documents. There are different applications of document clustering include automatic document organization, data mining , topic extraction and filtering or fast information retrieval. The purpose of this su...

Clustering is the process of grouping of data, where the grouping is established by finding similarities between data based on their characteristics. Such groups are termed as Clusters. Clustering is an unsupervised learning problem that group objects based upon distance or similarity. While a lot of work has been published on clustering of data on storage medium, little has been done about aut...