Fabrizio Angiulli
Rachel Ben-Eliyahu-Zohary
Abstract
Metaquerying is a data mining technology by which hidden dependencies among several database relations can be discovered. This tool has already been successfully applied to several real-world applications, but only preliminary results about the complexity of metaquerying can be found in the literature. In this article, we define several variants of metaquerying that encompass, as far as we know, all the variants that have been defined in the literature. We study both the combined complexity and the data complexity of these variants. We show that under the combined complexity measure metaquerying is generally intractable (unless P = NP), lying sometimes quite high in the complexity hierarchies (as high as NPPP), depending on the characteristics of the plausibility index. Nevertheless, we are able to single out some tractable and interesting metaquerying cases, whose combined complexity is LOGCFL-complete. As for the data complexity of metaquerying, we prove that, in general, it is within TC0, but lies within AC0 in some simpler cases. Finally, we discuss the implementation of metaqueries by providing algorithms that answer them.
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Index Terms
- Computational properties of metaquerying problems
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