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17th International Conference on Database and Expert Systems Applications (DEXA'06)
Automatic Database Clustering Using Data Mining
Krakow, Poland
September 04-September 08
ISBN: 0-7695-2641-1
Sylvain Guinepain, The University of Oklahoma, USA
Le Gruenwald, The University of Oklahoma, USA
Because of data proliferation, efficient access methods and data storage techniques have become increasingly critical to maintain an acceptable query response time. One way to improve query response time is to reduce the number of disk I/Os by partitioning the database vertically (attribute clustering) and/or horizontally (record clustering). A clustering is optimized for a given set of queries. However in dynamic systems the queries change with time, the clustering in place becomes obsolete, and the database needs to be re-clustered dynamically. In this paper we discuss an efficient algorithm1 for attribute clustering that dynamically and automatically generate attribute clusters based on closed item sets mined from the attributes sets found in the queries running against the database.
Citation:
Sylvain Guinepain, Le Gruenwald, "Automatic Database Clustering Using Data Mining," dexa, pp.124-128, 17th International Conference on Database and Expert Systems Applications (DEXA'06), 2006
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