Exception Rule Mining with a Relative Interestingness Measure-Reference-Cited by-同舟云学术

Exception Rule Mining with a Relative Interestingness Measure

Published:2000 Issue: Volume: Page:86-97
ISSN:0302-9743
Container-title:Knowledge Discovery and Data Mining. Current Issues and New Applications
language:
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Author:

Hussain Farhad,Liu Huan,Suzuki Einoshin,Lu Hongjun

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-45571-X_11

Reference16 articles.

1. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proc. 20th conference on Very Large Databases (VLDB), pages 478–499, 1994.

2. G. Piatetsky-Shapiro C. Matheus and D. McNeil. Selecting and Reporting What is Interesting: The KEFIR Application to Healthcare Data. AAAI Press/ MIT Press, 1996.

3. Sarawagi Chakrabarti. Mining surprising patterns using temporal description length. In Proc. 24th on Very Large Databases (VLDB), pages 606–616, 1998.

4. Liu H. and Lu H. Efficient search of reliable exceptions. In Proc. third Pacific-Asia conference on Knowledge Discovery and Data mining (PAKDD), pages 194–203, 1999.

5. W. Hsu Liu B. and Shu Chen. Using general impression to analyze discovered classification rules. In Proc. third international conference on Knowledge Discovery and Data mining (KDD), pages 31–36, 1997.

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