Discovering Multi-head Attributional Rules in Large Databases

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dc.contributor.authorGłowiński, Cezary
dc.contributor.authorMichalski, Ryszard S.
dc.date.accessioned2006-11-03T18:17:14Z
dc.date.available2006-11-03T18:17:14Z
dc.date.issued2001-06
dc.description.abstractA method for discovering multi-head attributional rules in large databases is presented and illustrated by results from an implemented program. Attributional rules (a.k.a. attributional dependencies) can be viewed as generalizations of standard association rules, because they use more general and expressive conditions than those in the latter ones, and by that can express more concisely inter-attribute relations in a database. Multi-head rules have multiple conditions/statements in their conclusion. The presented method applies AQ learning to create single-head characteristic rules, and then seeks conditions (selectors) that can be transferred to the conclusion part of the rule. Experiments with the program MAR1 (Multi-Head Attributional Rules), implementing the developed method, has produced highly encouraging results.
dc.description.sponsorshipCezary Głowiński has been supported by Kosciuszko Foundation in New York, in part by the National Science Foundation Grant IIS 9906858, and in part by the UMBC/MPO/Lucite #32 grant.
dc.format.extent2060 bytes
dc.format.extent237901 bytes
dc.format.extent61973 bytes
dc.format.mimetypetext/xml
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.identifier.citation(P 01-4) Glowinski, C. and Michalski, R. S., "Discovering Multi-head Attributional Rules in Large Databases," Tenth International Symposium on Intelligent Information Systems, Zakopane, Poland, June, 2001.
dc.identifier.urihttps://hdl.handle.net/1920/1475
dc.language.isoen_US
dc.relation.ispartofseriesP 01-4
dc.subjectAttributional rules
dc.titleDiscovering Multi-head Attributional Rules in Large Databases
dc.typePresentation

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