In this work, we present an interactive visual clustering approach for the exploration and analysis of vast volumes of data. The proposed approach is based on a bio-inspired collective behavioral model used in a 3D graphics environment. The paper illustrates an extension of the behavioral model for clustering and a parallel implementation using Compute Unified Device Architecture to exploit the computational power of Graphics Processor Unit. The advantage of this approach is that, as the data

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... ters in the environment, the user is directly involved in the data mining process. Our performance experiments illustrate the effectiveness and efficiency provided by our approach over a number of real and synthetic data sets.