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» Efficient Mining of Dissociation Rules
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KDD
2004
ACM
148views Data Mining» more  KDD 2004»
14 years 8 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
ICDE
2005
IEEE
146views Database» more  ICDE 2005»
14 years 9 months ago
Mining Evolving Customer-Product Relationships in Multi-Dimensional Space
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...
Xiaolei Li, Jiawei Han, Xiaoxin Yin, Dong Xin
CIB
2004
57views more  CIB 2004»
13 years 7 months ago
Identifying Global Exceptional Patterns in Multi-database Mining
In multi-database mining, there can be many local patterns (frequent itemsets or association rules) in each database. At the end of multi-database mining, it is necessary to analyz...
Chengqi Zhang, Meiling Liu, Wenlong Nie, Shichao Z...
ICDE
2008
IEEE
120views Database» more  ICDE 2008»
14 years 9 months ago
Direct Discriminative Pattern Mining for Effective Classification
The application of frequent patterns in classification has demonstrated its power in recent studies. It often adopts a two-step approach: frequent pattern (or classification rule) ...
Hong Cheng, Xifeng Yan, Jiawei Han, Philip S. Yu
IJNSEC
2010
112views more  IJNSEC 2010»
13 years 2 months ago
Detecting Connection-Chains: A Data Mining Approach
A connection-chain refers to a mechanism in which someone recursively logs into a host, then from there logs into another host, and so on. Connection-chains represent an important...
Ahmad Almulhem, Issa Traoré