Efficient evaluation of queries with mining predicates

Details Efficient evaluation of queries with mining predicates Efficient evaluation of queries with mining predicates

2008-03-18

2008-03-18

Mofiz, Apu (Department: 2161)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000

Reexamination Certificate

active

10161308

ABSTRACT:
A method for evaluating a user query on a database having a mining model that classifies records contained in the database into classes when the query comprises at least one mining predicate that refers to a class of database records. An upper envelope is derived for the class referred to by the mining predicate corresponding to a query that returns a set of database records that includes all of the database records belonging to the class. The upper envelope is included in the user query for query evaluation. The method may be practiced during a preprocessing phase by evaluating the mining model to extract a set of classes of the database records and deriving an upper envelope for each class. These upper envelopes are stored for access during user query evaluation.

REFERENCES:
patent: 6629095 (2003-09-01), Wagstaff et al.
patent: 6804669 (2004-10-01), Aggarwal
patent: 2002/0143755 (2002-10-01), Wynblatt et al.
SQL Multimedia and Application Packages Part 6: Data Mining, ISO Draft Recommendations, 1999.
R. Agrawal, J. Gehrke, D. Gunopulos and P. Raghavan, “Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications”, pp. 94-105, In Proceedings ACM SIGMOD International Conference on Management of Data, Seattle, WA, USA, Jun. 1998.
R. Agrawal, S. Ghosh, T. Imielinski, B. Iyer and A. Swami, “An Interval Classifier for Database Mining Applications”, pp. 560-573, Proceedings of the 18thVLDB Conference, Vancouver, British Columbia, Canada, 1992.
S. Agrawal, S. Chaudhuri, L. Kollar, V. Narasayya, Index Tuning Wizard for Microsoft SQL Server 2000, http://msdn.microsoft.com/library/techart/itwforsql.htm, 2000.
M. Berger and I. Regoutsos, “An Algorithm for Point Clustering and Grid Generation”, IEEE Transactions on Systems, Man and Cybernetics, vol. 21, No. 5, Sep./Oct. 1991, pp. 1278-1286, 1991.
S. Chaudhuri, “Data Mining and Database Systems: Where is the Intersection?”, Bulletin of Technical Committee on Data Engineering, vol. 21, pp. 1-5, Mar. 1998.
S. Chaudhuri and U. Dayal, “Data Warehousing and OLAP for Decision Support”, pp. 507-508, ACM SIGMOD Record, Mar. 1997.
S. Chaudhuri and V. Narasayya, “An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server”, In VLDB '97 Proceedings of 23rdInternational Conference on Very Large Data Bases, Aug. 1997, pp. 146-155.
S. Chaudhuri and K. Shim, “Optimization of Queries with User-Defined Predicates”, ACM Transactions on Database Systems, vol. 24, No. 2, Jun. 1999, pp. 177-228.
OLE DB for Data Mining, http://www.microsoft.com/data/oledb.
M. Ester, H.P. Kriegel, J. Sander, X. Xu, “A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise”, Proceedings of the 2ndInternational Conference on Knowledge Discovery in Databases and Data Mining, Aug. 1996.
J. Hellerstein, M. Stonebraker, “Predicate Migration: Optimizing Queries with expensive Predicates”, SIGMOD Conference, 1993, pp. 267-276.
S.J. Hong, R.G. Cain, D.L. Ostapko, “MINI: A Heuristic Approach for Logic Minimization”, Sep. 1974, pp. 443-458.
IBM Intelligent Miner Scoring, Administration and Programming for DB2, Version 7.1, Mar. 2001.
R. Meo, G. Psaila and S. Ceri, “An Extension to SQL for Mining Association Rules”, Data Mining and Knowledge Discovery, vol. 2, pp. 195-224, 1998.
R. Reckhow and J. Culberson, “Covering a Simple Orthogonal Polygon with a Minimum Number of Orthogonally Convex Polygons”, 1987, Proceedings of the ACM 3rdAnnual Computational Geometry Conference, pp. 268-277.
S. Sarawagi, S. Thomas and R. Agrawal, “Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications”, Proceedings ACM SIGMOD International Conference on Management of Data, Jun. 1998, pp. 343-354.
W. Scheufele and G. Moerkotte, “Efficient Dynamic Programming Algorithms for Ordering expensive Joins and Selections”, Proceedings of the 6thInternational Conference on Extending Database Technology, 1998, pp. 201-215.
Integrating Data Mining with SQL Databases: OLE DB for Data Mining, A. Netz, S. Chaudhuri, U. Fayyad, J. Bernhardt.

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