Supporting queries with imprecise constraints

Ullas Nambiar, Subbarao Kambhampati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In this paper, we motivate the need for and challenges involved in supporting imprecise queries over Web databases. Then we briefly explain our solution, AIMQ - a domain independent approach for answering imprecise queries that automatically learns query relaxation order by using approximate functional dependencies. We also describe our approach for learning similarity between values of categorical attributes. Finally, we present experimental results demonstrating the robustness, efficiency and effectiveness of AIMQ.

Original languageEnglish (US)
Title of host publicationProceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
Pages1654-1657
Number of pages4
StatePublished - Nov 13 2006
Event21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06 - Boston, MA, United States
Duration: Jul 16 2006Jul 20 2006

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume2

Other

Other21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
CountryUnited States
CityBoston, MA
Period7/16/067/20/06

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Nambiar, U., & Kambhampati, S. (2006). Supporting queries with imprecise constraints. In Proceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06 (pp. 1654-1657). (Proceedings of the National Conference on Artificial Intelligence; Vol. 2).