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» Data Mining: Machine Learning, Statistics, and Databases
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140
Voted
KDD
2009
ACM
163views Data Mining» more  KDD 2009»
16 years 4 months ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer
SIGMOD
2004
ACM
184views Database» more  SIGMOD 2004»
16 years 3 months ago
CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies
The rich dependency structure found in the columns of real-world relational databases can be exploited to great advantage, but can also cause query optimizers--which usually assum...
Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul B...
138
Voted
ISSRE
2007
IEEE
15 years 5 months ago
Data Mining Techniques for Building Fault-proneness Models in Telecom Java Software
This paper describes a study performed in an industrial setting that attempts to build predictive models to identify parts of a Java system with a high probability of fault. The s...
Erik Arisholm, Lionel C. Briand, Magnus Fuglerud
228
Voted
SIGMOD
2005
ACM
162views Database» more  SIGMOD 2005»
16 years 3 months ago
Fast and Approximate Stream Mining of Quantiles and Frequencies Using Graphics Processors
We present algorithms for fast quantile and frequency estimation in large data streams using graphics processor units (GPUs). We exploit the high computational power and memory ba...
Naga K. Govindaraju, Nikunj Raghuvanshi, Dinesh Ma...
129
Voted
SIGKDD
2010
125views more  SIGKDD 2010»
14 years 10 months ago
A framework for mining interesting pattern sets
This paper suggests a framework for mining subjectively interesting pattern sets that is based on two components: (1) the encoding of prior information in a model for the data min...
Tijl De Bie, Kleanthis-Nikolaos Kontonasios, Eirin...