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KDD
2004
ACM
148views Data Mining» more  KDD 2004»
16 years 7 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici
ICDM
2009
IEEE
162views Data Mining» more  ICDM 2009»
16 years 1 months ago
Accurate Estimation of the Degree Distribution of Private Networks
—We describe an efficient algorithm for releasing a provably private estimate of the degree distribution of a network. The algorithm satisfies a rigorous property of differenti...
Michael Hay, Chao Li, Gerome Miklau, David Jensen
DMIN
2009
223views Data Mining» more  DMIN 2009»
15 years 4 months ago
Are Decision Trees Always Greener on the Open (Source) Side of the Fence?
- This short paper compares the performance of three popular decision tree algorithms: C4.5, C5.0, and WEKA's J48. These decision tree algorithms are all related in that C5.0 ...
Samuel Moore, Daniel D'Addario, James Kurinskas, G...
GRC
2010
IEEE
15 years 7 months ago
Local Pattern Mining from Sequences Using Rough Set Theory
Abstract--Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns ...
Ken Kaneiwa, Yasuo Kudo
ISI
2005
Springer
16 years 2 days ago
Link Analysis Tools for Intelligence and Counterterrorism
Association rule mining is an important data analysis tool that can be applied with success to a variety of domains. However, most association rule mining algorithms seek to discov...
Antonio Badia, Mehmed M. Kantardzic