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» On Minimal Infrequent Itemset Mining
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KDD
2007
ACM
179views Data Mining» more  KDD 2007»
14 years 1 months ago
Mining statistically important equivalence classes and delta-discriminative emerging patterns
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
Jinyan Li, Guimei Liu, Limsoon Wong
KDD
1999
ACM
220views Data Mining» more  KDD 1999»
13 years 11 months ago
Efficient Mining of Emerging Patterns: Discovering Trends and Differences
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from...
Guozhu Dong, Jinyan Li
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
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
14 years 7 months ago
Reasoning about sets using redescription mining
Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. It can be viewed as a generalization of associa...
Mohammed Javeed Zaki, Naren Ramakrishnan
ICDE
2005
IEEE
118views Database» more  ICDE 2005»
14 years 8 months ago
A Framework for High-Accuracy Privacy-Preserving Mining
To preserve client privacy in the data mining process, a variety of techniques based on random perturbation of individual data records have been proposed recently. In this paper, ...
Shipra Agrawal, Jayant R. Haritsa