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» k-Selection Query over Uncertain Data
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SIGMOD
2008
ACM
169views Database» more  SIGMOD 2008»
14 years 7 months ago
MCDB: a monte carlo approach to managing uncertain data
To deal with data uncertainty, existing probabilistic database systems augment tuples with attribute-level or tuple-level probability values, which are loaded into the database al...
Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Per...
ICDE
2006
IEEE
204views Database» more  ICDE 2006»
14 years 8 months ago
Working Models for Uncertain Data
This paper explores an inherent tension in modeling and querying uncertain data: simple, intuitive representations of uncertain data capture many application requirements, but the...
Anish Das Sarma, Omar Benjelloun, Alon Y. Halevy, ...
EDBT
2008
ACM
180views Database» more  EDBT 2008»
14 years 7 months ago
Probabilistic ranked queries in uncertain databases
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, ...
Xiang Lian, Lei Chen 0002
ICDE
2007
IEEE
173views Database» more  ICDE 2007»
14 years 8 months ago
Top-k Query Processing in Uncertain Databases
Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between score and uncertainty makes traditio...
Mohamed A. Soliman, Ihab F. Ilyas, Kevin Chen-Chua...
CIKM
2006
Springer
13 years 10 months ago
Efficient join processing over uncertain data
In an uncertain database, each data item is modeled as a range associated with a probability density function. Previous works for this kind of data have focussed on simple queries...
Reynold Cheng, Sarvjeet Singh, Sunil Prabhakar, Ra...