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Vol: 47(61) No: 1 / March 2002 Mining Knowledge in Relational Databases Cornelia Gyorodi Department of Computer Science, Faculty of Electrotehnics and Informatics, University of Oradea, Str. Armatei Romane 5, 3700, Oradea, Romania, phone: +40 (0) 59 432-830, e-mail: cgyorodi@univ.uoradea.ro Stefan Holban Computer Science and Engineering Department, "Politehnica" University of Timisoara, Bd. Vasile Parvan 2, 1900, Timisoara, Romania, phone: +40 (0)256 204-333, e-mail: stefan@cs.utt.ro, web: http://www.cs.utt.ro/~stefan Robert Stefan Gyorodi Department of Electronic and Computer Engineering, University of Limerick, National Technological Park, Limerick, Ireland, phone: +353 (0) 61 212-095, e-mail: Robert.Gyorodi@ul.ie, web: http://www.ece.ul.ie/robert Mirela Pater Department of Computer Science, Faculty of Electrotehnics and Informatics, University of Oradea, Str. Armatei Romane 5, 3700, Oradea, Romania Keywords: Data mining, Knowledge discovery, DBMiner, OLAP. Abstract In recent years the size of databases has increased rapidly. For any database, the number of possible rules that can be extracted is far greater than the number of tuples in the database. Knowledge discovery is a multi-stage process of selecting interesting rules from the total rules of the total rule-space that exists within a database. In this paper we present the discovery process of various kinds of knowledge, at multiple concept levels, from large relational databases using DBMiner. References [1] Chris P. R., John F. R. “Databases issues in knowledge discovery and data mining”, Australian Journal of Information Systems, Vol. 6, 2000. [2] Jiawei Han, et al DBMiner: “DBMiner: A System for Data Mining in Relational Databases and Data Warehouses”, Proc. CASCON\'97: Meeting of Minds, Toronto, Canada, November 1997. [3] The Data Mining Research Group, “DBMiner Tutorial” Boeing Workshop, Seattle, Washington, December 1997. [4] http://db.cs.sfu.ca/DBMiner (for the DBMiner system) [5] Fayyad, U., M., et al. (1996). “From Data Mining to Knowledge Discovery: An Overview”. in Advances in Knowledge Discovery and Data Mining. AAAI Press/MIT Press. Pp.1-34 [6] Li, S. H., et al. (1997). “Discovering missing semantics from existing relational databases” . Eighth International Database Workshop, Data Mining. Hong Kong, Springer-Verlag Singapore. Pp.275-286. [7] J. Han, “OLAP Mining: An Integration of OLAP with Data Mining”, Proc. 1997 IFIP Conference on Data Semantics (DS-7), Leysin, Switzerland, Oct. 1997, pp. 1-11. [8]. Micheline Kamber, Jiawei Han, Jenny Y. Chiang, “Using Data Cubes for Metarule-Guided Mining of Multi-Dimensional Association Rules”, Techical Report CS-TR 97-10, School of Computing Science, Simon Fraser University, May 1997. [9] Jiawei Han, Micheline Kamber, “Data Mining Concepts and Techniques”, Morgan Kaufmann Publishers, San Francisco, USA,2001. |