TY - GEN
T1 - Supporting queries with imprecise constraints
AU - Nambiar, Ullas
AU - Kambhampati, Subbarao
PY - 2006/11/13
Y1 - 2006/11/13
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=33750717827&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33750717827&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33750717827
SN - 1577352815
SN - 9781577352815
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 1654
EP - 1657
BT - Proceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
T2 - 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
Y2 - 16 July 2006 through 20 July 2006
ER -