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» Mining Large Itemsets for Association Rules
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PAKDD
2004
ACM
94views Data Mining» more  PAKDD 2004»
14 years 23 days ago
Self-Similar Mining of Time Association Rules
Although the task of mining association rules has received considerable attention in the literature, algorithms to find time association rules are often inadequate, by either miss...
Daniel Barbará, Ping Chen, Zohreh Nazeri
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
JIS
2006
105views more  JIS 2006»
13 years 7 months ago
Automated support specification for efficient mining of interesting association rules
In recent years, the weakness of the canonical support-confidence framework for associations mining has been widely studied. One of the difficulties in applying association rules ...
Wen-Yang Lin, Ming-Cheng Tseng
KDD
1999
ACM
237views Data Mining» more  KDD 1999»
13 years 11 months ago
Using Association Rules for Product Assortment Decisions: A Case Study
It has been claimed that the discovery of association rules is well-suited for applications of market basket analysis to reveal regularities in the purchase behaviour of customers...
Tom Brijs, Gilbert Swinnen, Koen Vanhoof, Geert We...
FIMI
2004
175views Data Mining» more  FIMI 2004»
13 years 8 months ago
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Yudho Giri Sucahyo, Raj P. Gopalan