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数据挖掘双语教学课件2dw幻灯片.ppt

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* Data Mining: Concepts and Techniques * References (II) V. Harinarayan, A. Rajaraman, and J. D. Ullman. Implementing data cubes efficiently. In Proc. 1996 ACM-SIGMOD Int. Conf. Management of Data, pages 205-216, Montreal, Canada, June 1996. Microsoft. OLEDB for OLAP programmers reference version 1.0. In /data/oledb/olap, 1998. K. Ross and D. Srivastava. Fast computation of sparse datacubes. In Proc. 1997 Int. Conf. Very Large Data Bases, 116-125, Athens, Greece, Aug. 1997. K. A. Ross, D. Srivastava, and D. Chatziantoniou. Complex aggregation at multiple granularities. In Proc. Int. Conf. of Extending Database Technology (EDBT98), 263-277, Valencia, Spain, March 1998. S. Sarawagi, R. Agrawal, and N. Megiddo. Discovery-driven exploration of OLAP data cubes. In Proc. Int. Conf. of Extending Database Technology (EDBT98), pages 168-182, Valencia, Spain, March 1998. E. Thomsen. OLAP Solutions: Building Multidimensional Information Systems. John Wiley Sons, 1997. 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, 159-170, Tucson, Arizona, May 1997. * Data Mining: Concepts and Techniques * http://www.cs.sfu.ca/~han Thank you !!! * * * * * Data Mining: Concepts and Techniques * A Star-Net Query Model Shipping Method AIR-EXPRESS TRUCK ORDER Customer Orders CONTRACTS Customer Product PRODUCT GROUP PRODUCT LINE PRODUCT ITEM SALES PERSON DISTRICT DIVISION Organization Promotion CITY COUNTRY REGION Location DAILY QTRLY ANNUALY Time Each circle is called a footprint * Data Mining: Concepts and Techniques * Chapter 2: Data Warehousing and OLAP Technology for Data Mining What is a data warehouse? A multi-dimensional data model Data warehouse architecture Data warehouse implementation Further development of data cube technology From data warehousing to data mining * Data Mining: Concepts and Techniques * Design of a Data Warehouse: A Business Analysis Frame