In this paper, we propose a semi-supervised framework for learning a weighted Euclidean subspace, where the best clustering can be achieved. Our approach capitalizes on user-const...
Maria Halkidi, Dimitrios Gunopulos, Nitin Kumar, M...
Abstract. We introduce an automated multi-spectral MRI segmentation technique based on approximate reducts derived from the data mining paradigm of the theory of rough sets. We uti...
The paper combines and extends the technologies of fuzzy sets and association rules, considering users’ differential emphasis on each attribute through fuzzy regions. A fuzzy da...
Symbolic data analysis aims at generalizing some standard statistical data mining methods, such as those developed for classification tasks, to the case of symbolic objects (SOs). ...
The Internet and corporate intranets provide far more information than anybody can absorb. People use search engines to find the information they require. However, these systems t...