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Spectral clustering is one of the most effective methods of data mining, in which the adjacency matrix is constructed by using the similarity matrix. In this paper, to extend spectral clustering method for uncertain data clustering, we propose a new spectral clustering method based on JS-divergence. In the proposed method, the JS-divergence is used to construct the adjacency matrix in the spectral...
Different from current researches on Flickr group recommendation approaches that recommend groups to either users or images, this work proposes a unified framework that recommends groups to both users and images. Four types of entities in the Flickr system (users, tags, images, and groups) are integrated into a tetradic model, and then we uses tetradic decomposition to discover the latent semantic...
Uncertain data clustering is an essential task in the research of data mining. Lots of traditional clustering methods are extended with new similarity measurements to tackle this issue. Different from certain data clustering, uncertain data clustering focus more on the evaluation of distribution similarity between uncertain data objects. In this paper, based on the KL-divergence and the JS-divergence,...
Some studies have shown that coupled complex dynamical systems have more complex dynamics and wider application prospects compared with coupled real valued dynamical systems. The present paper formulates and studies a general model of networked coupled multi-valued complex dynamical systems. By analyzing the stability of syn- chronization manifold for such networked coupled complex dynamical systems,...
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