Modern enterprise applications are forced to deal with unreliable, inconsistent and imprecise information. Probabilistic databases can model such data naturally, but SQL query eva...
We propose efficient techniques for processing various TopK count queries on data with noisy duplicates. Our method differs from existing work on duplicate elimination in two sign...
Sunita Sarawagi, Vinay S. Deshpande, Sourabh Kasli...
On-Line Analytical Processing (OLAP) technologies are being used widely, but the lack of effective means of handling data imprecision, which occurs when exact values are not known...
Torben Bach Pedersen, Christian S. Jensen, Curtis ...
A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...
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 independe...