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» Further Pruning for Efficient Association Rule Discovery
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ICDM
2009
IEEE
134views Data Mining» more  ICDM 2009»
13 years 5 months ago
Efficient Discovery of Confounders in Large Data Sets
Given a large transaction database, association analysis is concerned with efficiently finding strongly related objects. Unlike traditional associate analysis, where relationships ...
Wenjun Zhou, Hui Xiong
HICSS
2003
IEEE
171views Biometrics» more  HICSS 2003»
14 years 25 days ago
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Ming-Yen Lin, Suh-Yin Lee
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
SAC
2005
ACM
14 years 1 months ago
Mining concept associations for knowledge discovery in large textual databases
In this paper, we describe a new approach for mining concept associations from large text collections. The concepts are short sequences of words that occur frequently together acr...
Xiaowei Xu, Mutlu Mete, Nurcan Yuruk
KDD
1998
ACM
136views Data Mining» more  KDD 1998»
13 years 11 months ago
Integrating Classification and Association Rule Mining
Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the dat...
Bing Liu, Wynne Hsu, Yiming Ma