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ICDM
2005
IEEE
151views Data Mining» more  ICDM 2005»
11 years 11 months ago
A Framework for Semi-Supervised Learning Based on Subjective and Objective Clustering Criteria
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...
TKDD
2008
75views more  TKDD 2008»
11 years 5 months ago
A clustering framework based on subjective and objective validity criteria
Maria Halkidi, Dimitrios Gunopulos, Michalis Vazir...
KDD
2010
ACM
279views Data Mining» more  KDD 2010»
11 years 9 months ago
Unifying dependent clustering and disparate clustering for non-homogeneous data
Modern data mining settings involve a combination of attributevalued descriptors over entities as well as specified relationships between these entities. We present an approach t...
M. Shahriar Hossain, Satish Tadepalli, Layne T. Wa...
MM
2010
ACM
219views Multimedia» more  MM 2010»
11 years 5 months ago
A framework for photo-quality assessment and enhancement based on visual aesthetics
We present an interactive application that enables users to improve the visual aesthetics of their digital photographs using spatial recomposition. Unlike earlier work that focuse...
Subhabrata Bhattacharya, Rahul Sukthankar, Mubarak...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
11 years 11 months ago
Combining partitions by probabilistic label aggregation
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
Tilman Lange, Joachim M. Buhmann
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