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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»
15 years 10 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
PKDD
2000
Springer
159views Data Mining» more  PKDD 2000»
15 years 1 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 3 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 3 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»
15 years 10 months 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...