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KDD
2012
ACM
247views Data Mining» more  KDD 2012»
13 years 9 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
EUROPAR
2004
Springer
15 years 10 months ago
Efficient Parallel Hierarchical Clustering
Hierarchical agglomerative clustering (HAC) is a common clustering method that outputs a dendrogram showing all N levels of agglomerations where N is the number of objects in the d...
Manoranjan Dash, Simona Petrutiu, Peter Scheuerman...
JPDC
2007
191views more  JPDC 2007»
15 years 6 months ago
Clustering wireless ad hoc networks with weakly connected dominating set
The increasing popular personal communications and mobile computing require a wireless network infrastructure that supports selfconfiguration and self-management. Efficient clus...
Bo Han, Weijia Jia
BILDMED
2011
245views Algorithms» more  BILDMED 2011»
14 years 10 months ago
Clustering-Based Detection of Anatomical Features on Organic Shapes
Abstract. Robust and accurate automatic detection of anatomical features on organic shapes is a challenging task. Despite a rough similarity, each shape is unique. To cope with thi...
Konrad Sickel, Vojtech Bubnik
KAIS
2006
126views more  KAIS 2006»
15 years 6 months ago
Fast and exact out-of-core and distributed k-means clustering
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
Ruoming Jin, Anjan Goswami, Gagan Agrawal