Tsur, S. and Ullman, J. and Abiteboul, S. and Clifton, C. and Motwani, R. and Nestorov, S. and Rosenthal, A. (1997) Query Flocks: a Generalization of Association-Rule Mining. Technical Report. Stanford InfoLab.
Association-rule mining has proved a highly successful technique for extracting useful information from very large databases. This success is attributed not only to the appropriateness of the objectives, but to the fact that a number of new query-optimization ideas, such as the "a-priori" trick, make association-rule mining run much faster than might be expected. In this paper we see that the same tricks can be extended to a much more general context, allowing effcient mining of very large databases for many different kinds of patterns. The general idea, called "query flocks," is a generate-and-test model for data-mining problems. We show how the idea can be used either in a general-purpose mining system or in a next generation of conventional query optimizers.
|Item Type:||Techreport (Technical Report)|
|Uncontrolled Keywords:||data mining, market-basket analysis, query optimization|
|Subjects:||Computer Science > Data Mining|
|Related URLs:||Project Homepage||http://infolab.stanford.edu/serf/|
|Deposited By:||Import Account|
|Deposited On:||25 Feb 2000 16:00|
|Last Modified:||04 Jan 2009 12:24|
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