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ICDM
2010
IEEE
147views Data Mining» more  ICDM 2010»
13 years 6 months ago
Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach
Whenever a dataset has multiple discrete target variables, we want our algorithms to consider not only the variables themselves, but also the interdependencies between them. We pro...
Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, M...
ICDM
2006
IEEE
118views Data Mining» more  ICDM 2006»
14 years 2 months ago
Reducing the Frequent Pattern Set
One of the major problems in frequent pattern mining is the explosion of the number of results, making it difficult to identify the interesting frequent patterns. In a recent pap...
Ronnie Bathoorn, Arne Koopman, Arno Siebes
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 9 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
WWW
2009
ACM
14 years 1 months ago
Extracting data records from the web using tag path clustering
Fully automatic methods that extract lists of objects from the Web have been studied extensively. Record extraction, the first step of this object extraction process, identifies...
Gengxin Miao, Jun'ichi Tatemura, Wang-Pin Hsiung, ...
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
14 years 9 months ago
Frequent pattern mining with uncertain data
In this paper, we will examine the frequent pattern mining for uncertain data sets. We will show how the broad classes of algorithms can be extended to the uncertain data setting....
Charu C. Aggarwal, Yan Li, Jianyong Wang, Jing Wan...