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Efficient mining of emerging patterns: discovering trends and differences
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Source 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: 43 - 52  
Year of Publication: 1999
ISBN:1-58113-143-7
Authors
Guozhu Dong  Department of CSE, Wright State University
Jinyan Li  Department of CSSE, The University of Melbourne
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
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Downloads (6 Weeks): 36,   Downloads (12 Months): 183,   Citation Count: 88
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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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C. Bettini, X. Sean Wang, and S. Jajodia. Mining temporal relationships with multiple granularities in time sequences. Data Engineering Bulletin, 21:32-38, 1998.
 
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G. Dong, J. Li and X. Zhang. Discovering Jumping Emerging Patterns and Experiments on Real Datasets. Proc. of 9th International Database Conference on Heterogeneous and internet Databases (IDC99), Hong Kong, 1999.
 
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G. Dong, X. Zhang, L. Wong, and J. Li. CAEP: Classification by Aggregating Emerging Patterns. Technical report, March 1999.
 
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J Han, G Dong, and Y Yin. Efficient mining of partial periodic patterns in time series database. In ICDE, 1999.
 
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J. Han, W. Gong, and Y. Yin. Mining segment-wise periodic patterns in time-related databases. In Proc. 1998 Int'l Conf. on Knowledge Discovery and Data Mining (KDD), 1998.
 
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B Lent, R Agrawal, and R Srikank. Discovering trends in text databases. In KDD 1997.
 
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J. Li, G. Dong, and K. Ramamohanarao. JEP- Classifier: Classification by Aggregating Jumping Emerging Patterns. Technical report, February 1999.
 
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H. Lu, J. Han, and L. Feng. Stock movement and n-dimensional inter-transaction association rules. In Proc. 1998 SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD'98), 1998.
 
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B Liu, W Hsu, and Y Ma. Integrating classification and association rule mining. In KDD 1998.
 
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H. Mannila, H Toivonen, and A. I. Verkamo. Discovering frequent episodes in sequences. In KDD 1995.
 
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Ron Rymon. Search through systematic set enumeration. In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning, 1992.

CITED BY  88