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ICDM
2005
IEEE
151views Data Mining» more  ICDM 2005»
14 years 29 days 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...
SDM
2004
SIAM
253views Data Mining» more  SDM 2004»
13 years 8 months ago
Density-Connected Subspace Clustering for High-Dimensional Data
Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...
Peer Kröger, Hans-Peter Kriegel, Karin Kailin...
DBA
2004
113views Database» more  DBA 2004»
13 years 8 months ago
A Quality Measure for Distributed Clustering
Clustering has become an increasingly important task in modern application domains. Mostly, the data are originally collected at different sites. In order to extract information f...
Eshref Januzaj, Hans-Peter Kriegel, Martin Pfeifle
AUSDM
2007
Springer
110views Data Mining» more  AUSDM 2007»
14 years 1 months ago
Useful Clustering Outcomes from Meaningful Time Series Clustering
Clustering time series data using the popular subsequence (STS) technique has been widely used in the data mining and wider communities. Recently the conclusion was made that it i...
Jason Chen
INCDM
2010
Springer
251views Data Mining» more  INCDM 2010»
13 years 11 months ago
Multi-Agent Based Clustering: Towards Generic Multi-Agent Data Mining
Abstract. A framework for Multi Agent Data Mining (MADM) is described. The framework comprises a collection of agents cooperating to address given data mining tasks. The fundamenta...
Santhana Chaimontree, Katie Atkinson, Frans Coenen