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» Mining Association Rules with Item Constraints
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VLDB
1998
ACM
147views Database» more  VLDB 1998»
13 years 11 months ago
Scalable Techniques for Mining Causal Structures
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...
Craig Silverstein, Sergey Brin, Rajeev Motwani, Je...
ICDE
2005
IEEE
146views Database» more  ICDE 2005»
14 years 8 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
ICSE
2004
IEEE-ACM
14 years 7 months ago
Mining Version Histories to Guide Software Changes
We apply data mining to version histories in order to guide programmers along related changes: "Programmers who changed these functions also changed...." Given a set of e...
Andreas Zeller, Peter Weißgerber, Stephan Di...
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
14 years 2 months ago
Mining Graph Evolution Rules
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
Michele Berlingerio, Francesco Bonchi, Björn ...
ICDM
2005
IEEE
177views Data Mining» more  ICDM 2005»
14 years 1 months ago
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases
In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represen...
Loïck Lhote, François Rioult, Arnaud S...