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» Approximate data mining in very large relational data
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ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
15 years 8 months ago
Scalable Algorithms for Distribution Search
Distribution data naturally arise in countless domains, such as meteorology, biology, geology, industry and economics. However, relatively little attention has been paid to data m...
Yasuko Matsubara, Yasushi Sakurai, Masatoshi Yoshi...
GECCO
2006
Springer
214views Optimization» more  GECCO 2006»
15 years 5 months ago
A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
SDM
2004
SIAM
194views Data Mining» more  SDM 2004»
15 years 3 months ago
Finding Frequent Patterns in a Large Sparse Graph
Graph-based modeling has emerged as a powerful abstraction capable of capturing in a single and unified framework many of the relational, spatial, topological, and other characteri...
Michihiro Kuramochi, George Karypis
AMINING
2003
Springer
261views Data Mining» more  AMINING 2003»
15 years 6 months ago
Micro View and Macro View Approaches to Discovered Rule Filtering
A data mining system can semi-automatically discover knowledge by mining a large volume of data, but the discovered knowledge is not always novel and may contain unreasonable facts...
Yasuhiko Kitamura, Akira Iida, Keunsik Park
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 2 months ago
Spatial scan statistics: approximations and performance study
Spatial scan statistics are used to determine hotspots in spatial data, and are widely used in epidemiology and biosurveillance. In recent years, there has been much effort invest...
Deepak Agarwal, Andrew McGregor, Jeff M. Phillips,...