Towards On-Line Analytical Mining in Large Databases

SIGMOD Record (ACM Special Interest Group on Management of Data)

Volumn 27, Issue 1, 1998, Pages 97-107

  Han, Jiawei ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0003060504     PISSN: 01635808     EISSN: None     Source Type: Journal    
DOI: 10.1145/273244.273273     Document Type: Article

References (33)

1. S. Agarwal, R. Agrawal, P. M. Deshpande, A. Gupta, J. F. Naughton, R. Ramakrishnan, and S. Sarawagi. On the computation of multidimensional aggregates. In Proc. 1996 Int. Conf. Very Large Data Bases, pages 506-521, Bombay, India, Sept. 1996.
2. R. Agrawal, K.-I. Lin, H.S. Sawhney, and K. Shim. Fast similarity search in the presence of noise, scaling, and translation in time-series databases. In Proc. 21st Int. Conf. Very Large Data Bases, pages 490-501, Zurich, Switzerland, Sept. 1995.
3. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proc. 1994 Int. Conf. Very Large Data Bases, pages 487-499, Santiago, Chile, September 1994.
4. Y. Cai, N. Cereone, and J. Han. Attribute-oriented induction in relational databases. In G. Piatetsky-Shapiro and W. J. Frawley, editors, Knowledge Discovery in Databases, pages 213-228. AAAI/MIT Press, 1991.
5. S. Chaudhuri and U. Dayal. An overview of data warehousing and OLAP technology. ACM SIGMOD Record, 26:65-74, 1997.
6. S. Cheng. Statistical approaches to predictive modeling in large databases. In M.Sc. Thesis, Simon Fraser University, Burnabv, B.C., Canada, January 1998.
7. D.W. Cheung, J. Han, V. Ng, A. Fu, and Y. Fu. A fast distributed algorithm for mining association rules. In Proc. 1996 Int. Conf. Parallel and Distributed Information Systems, pages 31-44, Miami Beach, Florida, Dec. 1996.
8. D.W. Cheung, J. Han, V. Ng, and C.Y. Wong. Maintenance of discovered association rules in large databases: An incremental updating technique. In Proc. 1996 Int'l Conf. Data Engineering, pages 106-114, New Orleans. Louisiana, Feb. 1996.
9. U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy. Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press, 1996.
10. Y. Fu and J. Han. Meta-rule-guided mining of association rules in relational databases. In Proc. 1st Int'l Workshop Integration of Knowledge Discovery with Deductive and Object-Oriented Databases (KDOOD'95), pages 39-46, Singapore, Dec. 1995.
11. W. Gong. Periodic pattern search in time-related data sets. In M.Sc. Thesis, Simon Fraser University, Burnaby, B.C., Canada, November 1997.
12. J. Han. OLAP mining: An integration of OLAP with data mining. In Proc. 1997 IFIP Conf. Data Semantics (DS-7), pages 1-11, Leysin, Switzerland, Oct. 1997.
13. J. Han, Y. Cai, and N. Cereone. Data-driven discovery of quantitative rules in relational databases. IEEE Trans. Knowledge and Data Engineering, 5:29-40, 1993.
14. J. Han, J. Chiang, S. Chee, J. Chen, Q. Chen, S. Cheng, W. Gong, M. Kamber, G. Liu, K. Koperski, Y. Lu, N. Stefanovic, L. Winstone, B. Xia, O. R. Zaïane, S. Zhang, and H. Zhu. DBMiner: A system for data mining in relational databases and data warehouses. In Proc. CASCON'97: Meeting of Minds, pages 249-260, Toronto, Canada, November 1997.
15. J. Han and Y. Fu. Discovery of multiple-level association rules from large databases. In Proc. 1995 Int. Conf. Very Large Data Bases, pages 420-431, Zurich, Switzerland, Sept. 1995.
16. J. Han and Y. Fu. Exploration of the power of attribute-oriented induction in data mining. In U.M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining, pages 399-421. AAAI/MIT Press, 1996.
17. J. Han, Y. Huang, N. Cereone, and Y. Fu. Intelligent query answering by knowledge discovery techniques. IEEE Trans. Knowledge and Data Engineering, 8:373-390, 1996.
18. J. Han and M. Kamber. Data Mining: Concepts and Techniques. in preparation, 1998.
19. J. Han, R. T. Ng, Y. Fu, and S. Dao. Dealing with semantic heterogeneity by generalization-based data mining techniques. In M. P. Papazoglou and G. Schlageter (eds.), Cooperative Information Systems: Current Trends & Directions, pages 207-231, Academic Press, 1998.
20. J. Han, S. Nishio, H. Kawano, and W. Wang. Generalization-based data mining in object-oriented databases using an object-cube model. In Data and Knowledge Engineering, to appear, 1998.
21. J. Han, N. Stefanovic, and K. Koperski. Selective materialization: An efficient method for spatial data cube construction. In Proc. 1998 Pacific-Asia Conf. Knowledge Discovery and Data Mining (PAKDD'98), Melbourne, Australia, April 1998.
22. M. Kamber, J. Han, and J. Y. Chiang. Metarule-guided mining of multi-dimensional association rules using data cubes. In Proc. 3rd Int. Conf. Knowledge Discovery and Data Mining (KDD'97), pages 207-210, Newport Beach, California, August 1997.
23. M. Kamber, L. Winstone, W. Gong, S. Cheng, and J. Han. Generalization and decision tree induction: Efficient classification in data mining. In Proc. of 1997 Int. Workshop Research Issues on Data Engineering (RIDE'97), pages 111-120, Birmingham, England, April 1997.
24. K. Koperski and J. Han. Discovery of spatial association rules in geographic information databases. In Proc. 4th Int'l Symp. Large Spatial Databases (SSD'95), pages 47-66, Portland, Maine, Aug. 1995.
25. M. Mehta, R. Agrawal, and J. Rissanen. SLIQ: A fast scalable classifier for data mining. In Proc. 1996 Int. Conf. Extending Database Technology (EDBT'96), Avignon, France, March 1996.
26. R. Ng and J. Han. Efficient and effective clustering method for spatial data mining. In Proc. 1994 Int. Conf. Very Large Data Bases, pages 144-155, Santiago, Chile, September 1994.
27. R. Ng, L. V. S. Lakshmanan, J. Han, and A. Pang. Exploratory mining and pruning optimizations of constrained associations rules. In submitted for publication, 1997.
28. J. R. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993.
29. R. Srikant and R. Agrawal. Mining generalized association rules. In Proc. 1995 Int. Conf. Very Large Data Bases, pages 407-419, Zurich, Switzerland, Sept. 1995.
30. B. Xia. Similarity search in time series data sets. In M.Sc. Thesis, Simon Fraser University, Burnaby, B.C., Canada, December 1997.
31. O. R. Zaïane, M. Xin, and J. Han. Discovering Web access patterns and trends by applying OLAP and data mining technology on Web logs. In Proc. Advances in Digital Libraries Conf. (ADL'98), Santa Babara, CA, April, 1998.
32. T. Zhang, R. Ramakrishnan, and M. Livny. BIRCH: an efficient data clustering method for very large databases. In Proc. 1996 ACM-SIGMOD Int. Conf. Management of Data, pages 103-114, Montreal, Canada, June 1996.
33. Y. Zhao, P. M. Deshpande, and J. F. Naughton. An array-based algorithm for simultaneous multidimensional aggregates. In Proc. 1997 ACM-SIGMOD Int. Conf. Management of Data, pages 159-170, Tucson, Arizona, May 1997.