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» Association Rule Mining Algorithms for Set-Valued Data
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PKDD
2005
Springer
138views Data Mining» more  PKDD 2005»
15 years 3 months ago
Indexed Bit Map (IBM) for Mining Frequent Sequences
Sequential pattern mining has been an emerging problem in data mining. In this paper, we propose a new algorithm for mining frequent sequences. It processes only one scan of the da...
Lionel Savary, Karine Zeitouni
KDD
2002
ACM
146views Data Mining» more  KDD 2002»
15 years 10 months ago
Closed Set Mining of Biological Data
We present a closed set data mining paradigm which is particularly e ective for uncovering the kind of deterministic, causal dependencies that characterize much of basic science. ...
John L. Pfaltz, Christopher M. Taylor
KDD
1999
ACM
108views Data Mining» more  KDD 1999»
15 years 2 months ago
Mining the Most Interesting Rules
Several algorithms have been proposed for finding the “best,” “optimal,” or “most interesting” rule(s) in a database according to a variety of metrics including confid...
Roberto J. Bayardo Jr., Rakesh Agrawal
PAKDD
2005
ACM
168views Data Mining» more  PAKDD 2005»
15 years 3 months ago
Adaptive Nonlinear Auto-Associative Modeling Through Manifold Learning
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
Junping Zhang, Stan Z. Li
ICDM
2002
IEEE
145views Data Mining» more  ICDM 2002»
15 years 2 months ago
Mining Top-K Frequent Closed Patterns without Minimum Support
In this paper, we propose a new mining task: mining top-k frequent closed patterns of length no less than min , where k is the desired number of frequent closed patterns to be min...
Jiawei Han, Jianyong Wang, Ying Lu, Petre Tzvetkov