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KDD
2004
ACM
150views Data Mining» more  KDD 2004»
16 years 2 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
16 years 1 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
DIAGRAMS
2004
Springer
15 years 7 months ago
Geographic Projection of Cluster Composites
A composite cluster map displays a fuzzy categorisation of geographic areas. It combines information from several sources to provide a visualisation of the significance of cluster...
Peter Kleiweg, John Nerbonne, Leonie Bosveld
108
Voted
SIGIR
2003
ACM
15 years 7 months ago
ReCoM: reinforcement clustering of multi-type interrelated data objects
Most existing clustering algorithms cluster highly related data objects such as Web pages and Web users separately. The interrelation among different types of data objects is eith...
Jidong Wang, Hua-Jun Zeng, Zheng Chen, Hongjun Lu,...
122
Voted
ICPR
2008
IEEE
16 years 3 months ago
Wavelet-based salient points with scale information for classification
The calculation of local features at points of interest is a vital part of many current image retrieval and object detection systems. The wavelet-based interest point detector by ...
Alexandra Teynor, Hans Burkhardt