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» Efficient Top-k Query Evaluation on Probabilistic Data
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ICDE
2007
IEEE
134views Database» more  ICDE 2007»
15 years 10 months ago
Efficient Top-k Query Evaluation on Probabilistic Data
Modern enterprise applications are forced to deal with unreliable, inconsistent and imprecise information. Probabilistic databases can model such data naturally, but SQL query eva...
Christopher Re, Nilesh N. Dalvi, Dan Suciu
ICDE
2009
IEEE
178views Database» more  ICDE 2009»
14 years 7 months ago
Efficient Query Evaluation over Temporally Correlated Probabilistic Streams
Many real world applications such as sensor networks and other monitoring applications naturally generate probabilistic streams that are highly correlated in both time and space. ...
Bhargav Kanagal, Amol Deshpande
EDBT
2009
ACM
208views Database» more  EDBT 2009»
15 years 4 months ago
Flexible and efficient querying and ranking on hyperlinked data sources
There has been an explosion of hyperlinked data in many domains, e.g., the biological Web. Expressive query languages and effective ranking techniques are required to convert this...
Ramakrishna Varadarajan, Vagelis Hristidis, Louiqa...
ICDE
2007
IEEE
137views Database» more  ICDE 2007»
15 years 10 months ago
SAO: A Stream Index for Answering Linear Optimization Queries
Linear optimization queries retrieve the top-K tuples in a sliding window of a data stream that maximize/minimize the linearly weighted sums of certain attribute values. To effici...
Gang Luo, Kun-Lung Wu, Philip S. Yu
SIGMOD
2003
ACM
145views Database» more  SIGMOD 2003»
15 years 9 months ago
Evaluating Probabilistic Queries over Imprecise Data
Many applications employ sensors for monitoring entities such as temperature and wind speed. A centralized database tracks these entities to enable query processing. Due to contin...
Reynold Cheng, Dmitri V. Kalashnikov, Sunil Prabha...