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ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
14 years 1 months ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
14 years 8 months ago
Dense itemsets
Frequent itemset mining has been the subject of a lot of work in data mining research ever since association rules were introduced. In this paper we address a problem with frequen...
Heikki Mannila, Jouni K. Seppänen
SIGMOD
1997
ACM
148views Database» more  SIGMOD 1997»
13 years 11 months ago
Beyond Market Baskets: Generalizing Association Rules to Correlations
One of the most well-studied problems in data mining is mining for association rules in market basket data. Association rules, whose significance is measured via support and confi...
Sergey Brin, Rajeev Motwani, Craig Silverstein
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 8 months ago
Identifying bridging rules between conceptual clusters
1 A bridging rule in this paper has its antecedent and action from different conceptual clusters. We first design two algorithms for mining bridging rules between clusters in a dat...
Shichao Zhang, Feng Chen, Xindong Wu, Chengqi Zhan...
KAIS
2006
164views more  KAIS 2006»
13 years 7 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis