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» Finding Interesting Associations without Support Pruning
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SIGMOD
1997
ACM
148views Database» more  SIGMOD 1997»
15 years 2 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
SIGMOD
1997
ACM
134views Database» more  SIGMOD 1997»
15 years 2 months ago
Scalable Parallel Data Mining for Association Rules
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consu...
Eui-Hong Han, George Karypis, Vipin Kumar
ICDE
2008
IEEE
158views Database» more  ICDE 2008»
15 years 11 months ago
CARE: Finding Local Linear Correlations in High Dimensional Data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
Xiang Zhang, Feng Pan, Wei Wang
AUSAI
2005
Springer
15 years 3 months ago
K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining
Most data-mining techniques seek a single model that optimizes an objective function with respect to the data. In many real-world applications several models will equally optimize...
Geoffrey I. Webb
KAIS
2006
164views more  KAIS 2006»
14 years 10 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis