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AAAI
1997
15 years 8 months ago
Efficient Management of Very Large Ontologies
This paper describes an environment for supporting very large ontologies. The system can be used on single PCs, workstations, a cluster of workstations, and high-end parallel supe...
Kilian Stoffel, Merwyn G. Taylor, James A. Hendler
IS
2008
15 years 6 months ago
A dimensionality reduction technique for efficient time series similarity analysis
We propose a dimensionality reduction technique for time series analysis that significantly improves the efficiency and accuracy of similarity searches. In contrast to piecewise c...
Qiang Wang, Vasileios Megalooikonomou
ICPR
2002
IEEE
16 years 7 months ago
Fast Hierarchical Clustering Based on Compressed Data
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Erendira Rendon, Ricardo Barandela
SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
15 years 8 months ago
Clustering with Bregman Divergences
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhil...
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
15 years 8 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar