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Quantitative evaluation of approximate frequent pattern mining algorithms
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Authors:
Rohit Gupta
Univ. of Minnesota, Twin Cities, Minneapolis, MN, USA
Gang Fang
Univ. of Minnesota, Twin Cities, Minneapolis, MN, USA
Blayne Field
Univ. of Wisconsin, Madison, Madison, WI, USA
Michael Steinbach
Univ. of Minnesota, Twin Cities, Minneapolis, MN, USA
Vipin Kumar
Univ. of Minnesota, Twin Cities, Minneapolis, MN, USA
2008 Article
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Published in:
· Proceeding
KDD '08
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Pages 301-309
ACM
New York, NY
, USA
©2008
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ISBN: 978-1-60558-193-4
doi>
10.1145/1401890.1401930
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Tags:
algorithms
approximate frequent itemsets
association analysis
data mining
error tolerance
experimentation
performance
performance measures
quantitative evaluation
verification
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