Abstract— In this paper, we propose a novel, effective and efficient probabilistic pruning criterion for probabilistic similarity queries on uncertain data. Our approach support...
Thomas Bernecker, Tobias Emrich, Hans-Peter Kriege...
Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between query scores and data uncertainty ma...
Mohamed A. Soliman, Ihab F. Ilyas, Kevin Chen-Chua...
Probabilistic databases have received considerable attention recently due to the need for storing uncertain data produced by many real world applications. The widespread use of pr...
— A paramount challenge in probabilistic databases is the scalable computation of confidences of tuples in query results. This paper introduces an efficient secondary-storage o...
In many applications, users specify target values for certain attributes, without requiring exact matches to these values in return. Instead, the result to such queries is typical...