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Previous clustering ensemble algorithms usually use a consensus function to obtain a final partition from the outputs of the initial clustering. In this paper, we propose a new clustering ensemble method, which generates a new feature space from initial clustering outputs. Multiple runs of an initial clustering algorithm like k-means generate a new feature(More)
Clustering ensembles have emerged as a powerful method for improving both the robustness and the stability of unsupervised classification solutions. However, finding a consensus clustering from multiple partitions is a difficult problem that can be approached from graph-based, combinatorial or statistical perspectives. We offer a probabilistic model of(More)
Hybrid CDN-P2P networks blend CDN and P2P technology to benefit from the complementary advantages of these technologies. In these networks, a critical challenge is to construct and maintain multicasting trees to distribute the content from distribution servers to the edge servers, clients and peers. In this work considering tight relation between internal(More)
In this paper, a new combinational method for improving the recognition rate of multiclass classifiers is proposed. The main idea behind this method is using pairwise classifiers to enhance the ensemble. Because of more accuracy of them, they can decrease the error rate in error-prone feature space. Firstly, a multiclass classifier has been trained. Then,(More)
Hybrid CDN-P2P networks blend Content Delivery Networks (CDN) and Peer-to-Peer (P2P) networks to overcome their shortcomings. Replica placement in these networks is still an open problem. Hierarchical structure of these networks makes it inefficient to use available replica placement strategies specialized to CDN or P2P network domains. In this work, we(More)
we propose that bio-inspired algorithms are best developed and analyzed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well founded analytical principles. we outline such a framework here, in the context of bio-inspired congestion control (BICC) models, and discuss mathematical techniques for(More)