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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 9 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
CLUSTER
2002
IEEE
14 years 2 months ago
Leveraging Standard Core Technologies to Programmatically Build Linux Cluster Appliances
Clusters have made the jump from lab prototypes to fullfledged production computing platforms. The number, variety, and specialized configurations of these machines are increasi...
Mason J. Katz, Philip M. Papadopoulos, Greg Bruno
KDD
2001
ACM
196views Data Mining» more  KDD 2001»
14 years 9 months ago
Efficient discovery of error-tolerant frequent itemsets in high dimensions
We present a generalization of frequent itemsets allowing the notion of errors in the itemset definition. We motivate the problem and present an efficient algorithm that identifie...
Cheng Yang, Usama M. Fayyad, Paul S. Bradley
CIKM
2009
Springer
14 years 3 months ago
Networks, communities and kronecker products
Emergence of the web and online computing applications gave rise to rich large scale social activity data. One of the principal challenges then is to build models and understandin...
Jure Leskovec
ICASSP
2008
IEEE
14 years 3 months ago
Audio retrieval by latent perceptual indexing
We present a query-by-example audio retrieval framework by indexing audio clips in a generic database as points in a latent perceptual space. First, feature-vectors extracted from...
Shiva Sundaram, Shrikanth Narayanan