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» ProUD: Probabilistic Ranking in Uncertain Databases
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SIGMOD
2007
ACM
176views Database» more  SIGMOD 2007»
14 years 6 months ago
URank: formulation and efficient evaluation of top-k queries in uncertain databases
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...
ICDE
2009
IEEE
214views Database» more  ICDE 2009»
14 years 8 months ago
Ranking with Uncertain Scores
Large databases with uncertain information are becoming more common in many applications including data integration, location tracking, and Web search. In these applications, ranki...
Mohamed A. Soliman, Ihab F. Ilyas
SSDBM
2006
IEEE
122views Database» more  SSDBM 2006»
14 years 10 days ago
Probabilistic Ranking Queries on Gaussians
In many modern applications, there are no exact values available to describe the data objects. Instead, the feature values are considered to be uncertain. This uncertainty is mode...
Christian Böhm, Alexey Pryakhin, Matthias Sch...
SSD
2005
Springer
175views Database» more  SSD 2005»
13 years 11 months ago
Probabilistic Spatial Queries on Existentially Uncertain Data
We study the problem of answering spatial queries in databases where objects exist with some uncertainty and they are associated with an existential probability. The goal of a thre...
Xiangyuan Dai, Man Lung Yiu, Nikos Mamoulis, Yufei...
ICDE
2010
IEEE
248views Database» more  ICDE 2010»
13 years 10 months ago
MashRank: Towards uncertainty-aware and rank-aware mashups
Mashups are situational applications that build data flows to link the contents of multiple Web sources. Often times, ranking the results of a mashup is handled in a materializethe...
Mohamed A. Soliman, Mina Saleeb, Ihab F. Ilyas