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» kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
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KDD
2004
ACM
148views Data Mining» more  KDD 2004»
16 years 4 days 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
PKDD
2000
Springer
159views Data Mining» more  PKDD 2000»
15 years 3 months ago
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
Abstract. This paper proposes a novel approach named AGM to eciently mine the association rules among the frequently appearing substructures in a given graph data set. A graph tran...
Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda
HICSS
2006
IEEE
149views Biometrics» more  HICSS 2006»
15 years 5 months ago
An Efficient Heuristic Search for Real-Time Frequent Pattern Mining
Real-time frequent pattern mining for business intelligence systems are currently in the focal area of research. In a number of areas of doing business, especially in the arena of...
Rajanish Dass, Ambuj Mahanti
ICDM
2007
IEEE
166views Data Mining» more  ICDM 2007»
15 years 6 months ago
Mining Statistical Information of Frequent Fault-Tolerant Patterns in Transactional Databases
Constraints applied on classic frequent patterns are too strict and may cause interesting patterns to be missed. Hence, researchers have proposed to mine a more relaxed version of...
Ardian Kristanto Poernomo, Vivekanand Gopalkrishna...
KDD
2008
ACM
246views Data Mining» more  KDD 2008»
16 years 4 days ago
Direct mining of discriminative and essential frequent patterns via model-based search tree
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...