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Towards Efficient Metaquery Generator

9 pagesPublished: November 18, 2018


Metaquery (MQ) is a datamining tool for inferring relations between data items over a relational database. The concept of MQ leads to autonomous discovery of logical rules involving the database tables. A central module of any MQ system is the MQ generator, which automatically generates all possible MQs to be tested against a database. The MQ generator is supposed to work in an efficient manner, while not missing any meaningful MQ. In this paper we present an algorithm for MQ generation that works as a search algorithm in which the states are all possible MQs, and the search tree is pruned whenever possible. Preliminary experiments prove that, indeed, the approach we take leads to a significant reduction in computation resources.

Keyphrases: Data Mining, metaqueries, relational database

In: Gilles Barthe, Konstantin Korovin, Stephan Schulz, Martin Suda, Geoff Sutcliffe and Margus Veanes (editors). LPAR-22 Workshop and Short Paper Proceedings, vol 9, pages 49--57

BibTeX entry
  author    = {Tamar Bash and Rachel Ben-Eliyahu-Zohary},
  title     = {Towards Efficient Metaquery Generator},
  booktitle = {LPAR-22 Workshop and Short Paper Proceedings},
  editor    = {Gilles Barthe and Konstantin Korovin and Stephan Schulz and Martin Suda and Geoff Sutcliffe and Margus Veanes},
  series    = {Kalpa Publications in Computing},
  volume    = {9},
  pages     = {49--57},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2515-1762},
  url       = {},
  doi       = {10.29007/xxcr}}
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