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CIKM
2006
Springer
15 years 3 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
APPINF
2003
15 years 1 months ago
Fast Frequent Itemset Mining using Compressed Data Representation
Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is compu...
Raj P. Gopalan, Yudho Giri Sucahyo
KDD
1999
ACM
217views Data Mining» more  KDD 1999»
15 years 4 months ago
An Efficient Algorithm to Update Large Itemsets with Early Pruning
We present an efficient algorithm (UWEP) for updating large itemsets when new transactions are added to the set of old transactions. UWEP employs a dynamic lookahead strategy in u...
Necip Fazil Ayan, Abdullah Uz Tansel, M. Erol Arku...
ADC
2003
Springer
182views Database» more  ADC 2003»
15 years 5 months ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
KDD
1997
ACM
135views Data Mining» more  KDD 1997»
15 years 3 months ago
Brute-Force Mining of High-Confidence Classification Rules
This paper investigates a brute-force technique for mining classification rules from large data sets. We employ an association rule miner enhanced with new pruning strategies to c...
Roberto J. Bayardo Jr.