Interactive Clustering in Distributed Environment

Abstract

Due to the explosion in the number of autonomous data sources, there is a growing need for effective approaches to distributed knowledge discovery and interactive data mining. In this paper, distributed VISTA system is proposed by extending existing visual cluster rendering system for distributed environment. First, all objects of local datasets are grouped using VISTA system and resulting centroids are considered as local models. Then, local models are combined to form a global model using VISTA. Finally, global clusters are automatically identified using global models and corresponding objects are visually explored. The experiments are carried out for various datasets of UCI machine learning data repository.