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» Mining Large Itemsets for Association Rules
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EMS
2008
IEEE
14 years 1 months ago
A Weighted Utility Framework for Mining Association Rules
Association rule mining (ARM) identifies frequent itemsets from databases and generates association rules by assuming that all items have the same significance and frequency of oc...
M. Sulaiman Khan, Maybin K. Muyeba, Frans Coenen
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
VLDB
1995
ACM
195views Database» more  VLDB 1995»
13 years 11 months ago
Discovery of Multiple-Level Association Rules from Large Databases
Previous studies on mining association rules find rules at single concept level, however, mining association rules at multiple concept levels may lead to the discovery of more spe...
Jiawei Han, Yongjian Fu
CIKM
2006
Springer
13 years 11 months ago
An integer programming approach for frequent itemset hiding
The rapid growth of transactional data brought, soon enough, into attention the need of its further exploitation. In this paper, we investigate the problem of securing sensitive k...
Aris Gkoulalas-Divanis, Vassilios S. Verykios
DMKD
2004
ACM
136views Data Mining» more  DMKD 2004»
14 years 25 days ago
Mining association rules with non-uniform privacy concerns
Privacy concerns have become an important issue in data mining. A popular way to preserve privacy is to randomize the dataset to be mined in a systematic way and mine the randomiz...
Yi Xia, Yirong Yang, Yun Chi