Data Warehousing and Knowledge Discovery: Third - download pdf or read online

By Larry Kerschberg (auth.), Yahiko Kambayashi, Werner Winiwarter, Masatoshi Arikawa (eds.)

ISBN-10: 3540425535

ISBN-13: 9783540425533

Data Warehousing and data Discovery expertise is rising as a key expertise for companies that desire to increase their information research, choice help actions, and the automated extraction of information from info. the target of the 3rd overseas convention on facts Warehousing and information Discovery (DaWaK 2001) used to be to compile researchers and practitioners to debate study matters and event in constructing and deploying info warehousing and information discovery platforms, functions, and recommendations. The convention concerned about the logical and actual layout of information warehousing and information discovery platforms. The scope of the papers lined the newest and suitable subject matters within the parts of organization principles, mining temporal styles, information mining concepts, collaborative filtering, net mining, visualization, matchmaking, evelopment and upkeep of knowledge warehouses, OLAP, and dispensed information warehouses. those complaints include the technical papers chosen for presentation on the convention. We bought greater than ninety papers from over 20 international locations, and this system committee eventually chosen 34 papers. The convention application integrated one invited speak: “Knowledge administration in Heterogeneous facts Warehouse Environments” through Professor Larry Kerschberg, George Mason college, USA.

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Additional resources for Data Warehousing and Knowledge Discovery: Third International Conference, DaWaK 2001 Munich, Germany, September 5–7, 2001 Proceedings

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R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In Proc. of the ACM SIGMOD Intl. Conf. on Management of Data, pages 207í216, 1993. 2. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proc. of the 20th Intl. Conf. on Very Large Data Bases, pages 478í499, 1994. 3. L. Feng, H. Lu, J. Yu, and J. Han. Mining inter-transaction association rules with templates. In Proc. ACM CIKM Intl. Conf. Information and Knowledge Management, pages 225í233, 1999.

Management of Data. (1997) 207-216 4. : Discovery of multiple-level association rules from large databases. Proc. 21st Int. Conf. Very Large Data Bases. Zurich, Swizerland (1995) 420-431 5. : Mining association rules with multiple minimum supports. Proc. 1999 Int. Conf. Knowledge Discovery and Data Mining. (1999) 337-341 6. : An effective hash-based algorithm for mining association rules. Proc. 1995 ACM-SIGMOD Int. Conf. Management of Data San Jose (1995) 175-186 7. : An efficient algorithm for mining association rules in large databases.

Agrawal, J. Shafer, "Parallel Mining of Association Rules," IEEE Transactions on Knowledge and Data Engineering, Vol. 8, No. 6, Dec. 1996. [4] C. Agrawal, and P. Yu, "Mining Large Itemsets for Association Rules," Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 1997. [5] A. Bookstein and W. Cooper, "A General Mathematical Model for Information Retrieval Systems," Library Quarterly, 46(2), 153-167. [6] S. Brin, R. Motwani, J. Ullman, and S. Tsur, "Dynamic Itemset Counting and Implication Rules for Market Basket Data," SIGMOD Record (SCM Special Interset Group on Management of Data), 26,2, 1997.

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Data Warehousing and Knowledge Discovery: Third International Conference, DaWaK 2001 Munich, Germany, September 5–7, 2001 Proceedings by Larry Kerschberg (auth.), Yahiko Kambayashi, Werner Winiwarter, Masatoshi Arikawa (eds.)


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