| An effective algorithm for mining interesting quantitative association rules |
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Symposium on Applied Computing
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Proceedings of the 1997 ACM symposium on Applied computing
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San Jose, California, United States
Pages: 88 - 90
Year of Publication: 1997
ISBN:0-89791-850-9
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Authors
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Keith C. C. Chan
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Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
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Wai-Ho Au
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Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
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Downloads (6 Weeks): 0, Downloads (12 Months): 28, Citation Count: 3
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REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Rakesh Agrawal , Tomasz Imieliński , Arun Swami, Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD international conference on Management of data, p.207-216, May 25-28, 1993, Washington, D.C., United States
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K. C. C. Chan, and A. K. C. Wong, "A Statistical Technique for Extracting Classificatory Knowledge from Databases", in G. Piatetsky-Shapiro, and W. J. Frawley (Eds.), Knowledge Discover3, in Databases, AAAI/MiT Press, 199 I, pp. 107-123.
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