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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...
—Recently, many new applications, such as sensor data monitoring and mobile device tracking, raise up the issue of uncertain data management. Compared to “certain” data, the ...
— Emerging uncertain database applications often involve the cleansing (conditioning) of uncertain databases using additional information as new evidence for reducing the uncerta...
A formal semantics of uncertain databases typically takes an algebraic approach by mapping an uncertain database to a set of relational databases, or possible worlds. We present a...
I started my PhD studies in March 2008 under the joint supervision of Prof. Xuemin Lin and Dr. Wei Wang. My current research interests include spatial databases, uncertain database...
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...
This work introduces novel polynomial algorithms for processing top-k queries in uncertain databases under the generally adopted model of x-relations. An x-relation consists of a n...
Ke Yi, Feifei Li, George Kollios, Divesh Srivastav...