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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 8 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
KDD
2008
ACM
163views Data Mining» more  KDD 2008»
14 years 8 months ago
The cost of privacy: destruction of data-mining utility in anonymized data publishing
Re-identification is a major privacy threat to public datasets containing individual records. Many privacy protection algorithms rely on generalization and suppression of "qu...
Justin Brickell, Vitaly Shmatikov
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 8 months ago
Assessing data mining results via swap randomization
The problem of assessing the significance of data mining results on high-dimensional 0?1 data sets has been studied extensively in the literature. For problems such as mining freq...
Aristides Gionis, Heikki Mannila, Panayiotis Tsapa...
KDD
2004
ACM
209views Data Mining» more  KDD 2004»
14 years 8 months ago
Tracking dynamics of topic trends using a finite mixture model
In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic tren...
Satoshi Morinaga, Kenji Yamanishi
SIGMOD
2009
ACM
140views Database» more  SIGMOD 2009»
14 years 8 months ago
Estimating the confidence of conditional functional dependencies
Conditional functional dependencies (CFDs) have recently been proposed as extensions of classical functional dependencies that apply to a certain subset of the relation, as specif...
Graham Cormode, Lukasz Golab, Flip Korn, Andrew Mc...