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» Parallel Mining of Maximal Frequent Itemsets from Databases
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DAWAK
2006
Springer
13 years 11 months ago
Two New Techniques for Hiding Sensitive Itemsets and Their Empirical Evaluation
Many privacy preserving data mining algorithms attempt to selectively hide what database owners consider as sensitive. Specifically, in the association-rules domain, many of these ...
Ahmed HajYasien, Vladimir Estivill-Castro
ICDE
2003
IEEE
146views Database» more  ICDE 2003»
14 years 9 months ago
Generalized Closed Itemsets for Association Rule Mining
The output of boolean association rule mining algorithms is often too large for manual examination. For dense datasets, it is often impractical to even generate all frequent items...
Vikram Pudi, Jayant R. Haritsa
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
14 years 8 months ago
Mining optimal decision trees from itemset lattices
We present DL8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. Because the discovery of optimal...
Élisa Fromont, Siegfried Nijssen
SIGMOD
2010
ACM
260views Database» more  SIGMOD 2010»
14 years 12 days ago
Towards proximity pattern mining in large graphs
Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
Arijit Khan, Xifeng Yan, Kun-Lung Wu
SDM
2011
SIAM
242views Data Mining» more  SDM 2011»
12 years 10 months ago
Fast Algorithms for Finding Extremal Sets
Identifying the extremal (minimal and maximal) sets from a collection of sets is an important subproblem in the areas of data-mining and satisfiability checking. For example, ext...
Roberto J. Bayardo, Biswanath Panda