Mining interesting knowledge using DM-II

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Mining interesting knowledge using DM-II

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International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents

San Diego, California, United States

Pages: 430 - 434

Year of Publication: 1999

ISBN:1-58113-143-7

Authors

Bing Liu	School of Computing, National University of Singapore, Lower Kent Ridge Road, Singapore 119260
Wynne Hsu	School of Computing, National University of Singapore, Lower Kent Ridge Road, Singapore 119260
Yiming Ma	School of Computing, National University of Singapore, Lower Kent Ridge Road, Singapore 119260
Shu Chen	School of Computing, National University of Singapore, Lower Kent Ridge Road, Singapore 119260

Sponsors

SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
AAAI : Am Assoc for Artifical Intelligence
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 6, Downloads (12 Months): 47, Citation Count: 2

Additional Information:

references cited by index terms collaborative colleagues peer to peer

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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.

	1	Rakesh Agrawal , Ramakrishnan Srikant, Fast Algorithms for Mining Association Rules in Large Databases, Proceedings of the 20th International Conference on Very Large Data Bases, p.487-499, September 12-15, 1994
	2	Agrawal, R. Mehta, M., Shafer, J. and and Srikant, R. "The Quest data mining system." KDD-96, 1996.
	3	Elder, J. F., and Abbott, D. M. A comparison of leading data mining tools. KDD.98 tutorial.
	4	Han, J., Fu, Y., Wang, W., Chiang, J., Gong, W. Koperski, K. Li, D., Lu, Y. Rajan, A., Stefanovic, N. Xia, B., Zaiane, O. "DBMiner: A system for mining knowledge in large relational databases." KDD-96, 1996.
	5	Mika Klemettinen , Heikki Mannila , Pirjo Ronkainen , Hannu Toivonen , A. Inkeri Verkamo, Finding interesting rules from large sets of discovered association rules, Proceedings of the third international conference on Information and knowledge management, p.401-407, November 29-December 02, 1994, Gaithersburg, Maryland, United States [doi>10.1145/191246.191314]
	6	Ron Kohavi , Dan Sommerfield , James Dougherty, Data Mining using MLC++, A Machine Learning Library in C++, Proceedings of the 8th International Conference on Tools with Artificial Intelligence (ICTAI '96), p.234, November 16-19, 1996
	7	Lee, W., Stolfo, S. J., and Mok, K. W. "Mining audit data to build intrusion detection models." KDD-98.
	8	Liu, B., Ku, L. P., and Hsu, W. "Discovering interesting Holes in Data." IJCAI-97, pp. 930-935.
	9	Liu, B., Hsu, W. "Post analysis of learned rules." AAAI-96, 1996.
	10	Liu, B., Hsu, W. and Ma, Y. M. "Integrating classification and association rule mining." KDD-98, 1998, pp. 80-86.
	11	Bing Liu , Wynne Hsu , Yiming Ma, Pruning and summarizing the discovered associations, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, p.125-134, August 15-18, 1999, San Diego, California, United States [doi>10.1145/312129.312216]
	12	Bing Liu , Wynne Hsu , Yiming Ma, Mining association rules with multiple minimum supports, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, p.337-341, August 15-18, 1999, San Diego, California, United States [doi>10.1145/312129.312274]
	13	Bing Liu , Wynne Hsu , Ke Wang , Shu Chen, Visually Aided Exploration of Interesting Association Rules, Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining, p.380-389, April 26-28, 1999
	14	Mills, F. Statistical Methods, Pitman, 1955.
	15	Padmanabhan, B., and Tuzhilin, A. "A belief-driven method for discovering unexpected patterns." KDD-98, 1998.
	16	J. Ross Quinlan, C4.5: programs for machine learning, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1993
	17	Avi Silberschatz , Alexander Tuzhilin, What Makes Patterns Interesting in Knowledge Discovery Systems, IEEE Transactions on Knowledge and Data Engineering, v.8 n.6, p.970-974, December 1996 [doi>10.1109/69.553165 ]

CITED BY 2

	Chieh-Yuan Tsai , Jing-Chung Wang , Chih-Jung Chen, A change detection model for credit card usage behavior, Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, p.276-281, November 20-22, 2006, Venice, Italy
	Szymon Jaroszewicz , Dan A. Simovici, Interestingness of frequent itemsets using Bayesian networks as background knowledge, Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, August 22-25, 2004, Seattle, WA, USA