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Semi-supervised clustering is a popular machine learning technique, used for challenge data categorization tasks, when some prior knowledge is available to users. In this paper, we report the empirical studies on our newly proposed semi-supervised clustering framework, which utilizes multiple viewpoints for the similarity measure, with the help of the prior knowledge. Two different MVS-based approaches...
Semi-supervised clustering uses a small amount of labeled data to aid and bias the clustering of unlabeled data. In this paper the use of labeled data at the initial state, as well as the use of the constraints generated from the labels during the clustering process is explored. We formulate the clustering process as a constrained optimization problem, and propose a novel semi-supervised fuzzy co-clustering...
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