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Metaqueries: Semantics, complexity, and efficient algorithms

delete2003-09-01
delete6
PRE
AI
R
Rachel Ben‐Eliyahu‐Zohary *
E
Ehud Gudes
G
Giovambattista Ianni
DOI:10.1016/S0004-3702(03)00073-0delete
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摘要

摘要

En 中文
Metaquery (metapattern) is a data mining tool which is useful for learning rules involving more than one relation in the database. The notion of a metaquery has been proposed as a template or a second-order proposition in a language C that describes the type of pattern to be discovered. This tool has already been successfully applied to several real-world applications. In this paper we advance the state of the art in metaquery research in several ways. First, we argue that the notion of a support value for metaqueries, where a support value is intuitively some indication to the relevance of the rules to be discovered, is not adequately defined in the literature, and, hence, propose our own definition. Second, we analyze some of the related computational problems, classify them as NP-hard and point out some tractable cases. Third, we propose some efficient algorithms for computing support and present preliminary experimental results that indicate the usefulness of our algorithms. (C) 2003 Elsevier B.V. All rights reserved.
Keyword:
knowledge discovery
data mining
metaqueries
support
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期刊

Artificial Intelligence Review 封面图
Artificial Intelligence Review
IF:
13.9
论文数:
6.1K
被引数:
1.9W

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