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An effective algorithm for mining interesting quantitative association rules
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Authors:
Keith C. C. Chan
Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Wai-Ho Au
Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Published in:
· Proceeding
SAC '97 Proceedings of the 1997 ACM symposium on Applied computing
Pages 88-90
ACM
New York, NY
, USA
©1997
table of contents
ISBN:0-89791-850-9
doi>
10.1145/331697.331714
1997 Article
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· Citation Count: 5
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Tags:
algorithms
data mining
data mining
design
experimentation
interestingness measure
negative association rules
performance
positive association rules
quantitative association rules
theory
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