Computational properties of metaquerying problems

Fabrizio Angiulli, Rachel Ben-Eliyahu-Zohary, Giovambattista Ianni, Luigi Palopoli

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


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 NP PP), 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 TC 0, but lies within AC 0 in some simpler cases. Finally, we discuss the implementation of metaqueries by providing algorithms that answer them.

Original languageEnglish
Pages (from-to)149-180
Number of pages32
JournalACM Transactions on Computational Logic
Issue number2
StatePublished - 1 Apr 2003


  • Computational complexity
  • Data mining

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science
  • Logic
  • Computational Mathematics


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