Ullas Nambiar, Subbarao Kambhampati
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.
Subjects: 1.10 Information Retrieval; 12. Machine Learning and Discovery