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» Mining Very Large Databases
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134
Voted
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 4 months ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen
KDD
2007
ACM
167views Data Mining» more  KDD 2007»
16 years 4 months ago
Multiscale topic tomography
Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...
Ramesh Nallapati, Susan Ditmore, John D. Lafferty,...
149
Voted
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
16 years 4 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu
EDBT
2010
ACM
184views Database» more  EDBT 2010»
15 years 10 months ago
Aggregation of asynchronous electric power consumption time series knowing the integral
More and more data mining algorithms are applied to a large number of long time series issued by many distributed sensors. The consequence of the huge volume of data is that data ...
Raja Chiky, Laurent Decreusefond, Georges Hé...
AUSDM
2007
Springer
102views Data Mining» more  AUSDM 2007»
15 years 7 months ago
A Two-Step Classification Approach to Unsupervised Record Linkage
Linking or matching databases is becoming increasingly important in many data mining projects, as linked data can contain information that is not available otherwise, or that woul...
Peter Christen