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KDD
2006
ACM
129views Data Mining» more  KDD 2006»
15 years 10 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
TEC
2008
104views more  TEC 2008»
14 years 9 months ago
Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy
Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction data i...
Tzung-Pei Hong, Chun-Hao Chen, Yeong-Chyi Lee, Yu-...
KDD
2012
ACM
194views Data Mining» more  KDD 2012»
13 years 6 days ago
A sparsity-inducing formulation for evolutionary co-clustering
Traditional co-clustering methods identify block structures from static data matrices. However, the data matrices in many applications are dynamic; that is, they evolve smoothly o...
Shuiwang Ji, Wenlu Zhang, Jun Liu
ICDE
1995
IEEE
139views Database» more  ICDE 1995»
15 years 11 months ago
Set-Oriented Mining for Association Rules in Relational Databases
We describe set-oriented algorithms for mining association rules. Such algorithms imply performing multiple joins and may appear to be inherently less escient than special-purpose...
Maurice A. W. Houtsma, Arun N. Swami
CIKM
2008
Springer
14 years 11 months ago
Probabilistic polyadic factorization and its application to personalized recommendation
Multiple-dimensional, i.e., polyadic, data exist in many applications, such as personalized recommendation and multipledimensional data summarization. Analyzing all the dimensions...
Yun Chi, Shenghuo Zhu, Yihong Gong, Yi Zhang