Frequent itemset counting using clustered prefixes and index...

Data processing: database and file management or data structures – Database design – Database and data structure management

Reexamination Certificate

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C707S687000

Reexamination Certificate

active

07962526

ABSTRACT:
Techniques are provided for (1) extending SQL to support direct invocation of frequent itemset operations, (2) improving the performance of frequent itemset operations by clustering itemset combinations to more efficiently use previously produced results, and (3) making on-the-fly selection of the occurrence counting technique to use during each phase of a multiple phase frequent itemset operation. When directly invoked in an SQL statement, a frequent itemset operation may receive input from results of operations specified in the SQL statement, and provide its results directly to other operations specified in the SQL statement. By clustering itemset combinations, resources may be used more efficiently by retaining intermediate information as long as it is useful, and then discarding it to free up volatile memory. Dynamically selecting an occurrence counting technique allows a single frequent itemset operation to change the occurrence counting technique that it is using midstream, based on cost considerations and/or environmental conditions.

REFERENCES:
patent: 5259066 (1993-11-01), Schmidt
patent: 5724573 (1998-03-01), Agrawal et al.
patent: 5794209 (1998-08-01), Agrawal et al.
patent: 6049797 (2000-04-01), Guha et al.
patent: 6138117 (2000-10-01), Bayardo
patent: 6192374 (2001-02-01), Lawrence
patent: 6324533 (2001-11-01), Agrawal et al.
patent: 6415287 (2002-07-01), Wang et al.
patent: 6453404 (2002-09-01), Bereznyi et al.
patent: 6473757 (2002-10-01), Garofalakis et al.
patent: 6490582 (2002-12-01), Fayyad et al.
patent: 6507843 (2003-01-01), Dong et al.
patent: 6567936 (2003-05-01), Yang et al.
patent: 6665669 (2003-12-01), Han et al.
patent: 6760718 (2004-07-01), Tamura
patent: 6832216 (2004-12-01), Shintani et al.
patent: 6993534 (2006-01-01), Denesuk et al.
patent: 6996551 (2006-02-01), Hellerstein et al.
patent: 2002/0073019 (2002-06-01), Deaton
patent: 2002/0087561 (2002-07-01), Chen et al.
patent: 2002/0116457 (2002-08-01), Eshleman et al.
patent: 2003/0149554 (2003-08-01), Lambert et al.
patent: 2004/0225742 (2004-11-01), Loaiza et al.
patent: 2005/0149540 (2005-07-01), Chan et al.
patent: 2006/0004807 (2006-01-01), Cruanes et al.
Gösta Grahne & J. Zhu, High Performance Mining of Maximal Frequent Itemsets. Mar. 22, 2003, 6th International Workshop on High Performance Data Mining (HPDM '03).
Written Opinion from PCT Patent Application No. PCT/US02/06981 dated Oct. 3, 2004(8 pgs.).
Current Claims in PCT Patent Application No. PCT/US02/06981 (8 pgs.).
Office Action from Canadian Patent Application No. 2,448,050 dated Oct. 1, 2004 (2 pgs).
Current Claims in Canadian Patent Application No. 2, 448,050 (48 pgs).
Wei Li, et al.,“Computing Frequent Itemsets Inside Oracle 10G”, Proceedings of the 30thVLDB Conference, Toronto, Canada, Aug. 29, 2004, 4 pages.
Oracle Corporation, “Oracle® Data Mining, Concepts,” l0g Release 1 (10.1), Part No. B10698-01, Dec. 2003, 118 pages.
Office Action from European Patent Application No. 01968979.3-2212, dated Aug. 6, 2004 (3 pgs.).
Current Claims in European Patent Application No. 01968979.3-2212 (3 pgs).
Agrawal, Rakesh et al., “Mining Association Rules Between Sets of Items in Large Database,” SIGMOND—1993, ACM Issue 2, vol. 22, pp. 207-216.
Burdick, Doug et al., “MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases,” 17thInternational Conference on Data Engineering-2001, retrieved fromhttp://www.almaden.ibm/cs/projects/lis/hdp/Publications/papers/sigmond93.pdf, pp. 1-6.
Grahne, Gösta et al., “High Performance Mining in Maximal Frequent Itemsets,” May 17, 2005, retrieved from the internet at http://www.cs.concordia.ca/db/dbdm/hpdm/hpdm03.pdf, 10 pages.
Agrawal et al., “Mining Association Rules between Sets of Items in Large Databases”, Proceedings of the 1993 ACM SIGMOD Conference, May 1993, 10 pages.
Rantzau, R., “Processing Frequent Itemset Discovery Queries by Division and Set Containment Join Operators”, DMKD 2003, Jun. 13, 2003, 8 pages.
Agrawal et al., “Fast Algorithms for Mining Association Rules”, In Proceedings of the Twentieth International Conference on Very Large Databases, 1994, 32 pages.
Garadin et al., Data & Knowledge Engineering, vol. 46, Issue 1, Jul. 2003, pp. 97-121.

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