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» Efficient Top-k Query Evaluation on Probabilistic Data
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ICDE
2008
IEEE
563views Database» more  ICDE 2008»
16 years 9 months ago
Probabilistic Verifiers: Evaluating Constrained Nearest-Neighbor Queries over Uncertain Data
In applications like location-based services, sensor monitoring and biological databases, the values of the database items are inherently uncertain in nature. An important query fo...
Reynold Cheng, Jinchuan Chen, Mohamed F. Mokbel, C...
ICDE
2007
IEEE
158views Database» more  ICDE 2007»
15 years 10 months ago
Efficient Evaluation of Imprecise Location-Dependent Queries
In location-based services, it is common for a user to issue a query based on his/her current position. One such example is "find the available cabs within two miles of my cu...
Jinchuan Chen, Reynold Cheng
ICDE
2011
IEEE
215views Database» more  ICDE 2011»
14 years 1 months ago
Top-k keyword search over probabilistic XML data
—Despite the proliferation of work on XML keyword query, it remains open to support keyword query over probabilistic XML data. Compared with traditional keyword search, it is far...
Jianxin Li, Chengfei Liu, Rui Zhou, Wei Wang
SIGMOD
2007
ACM
176views Database» more  SIGMOD 2007»
15 years 9 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...
97
Voted
VLDB
2004
ACM
98views Database» more  VLDB 2004»
15 years 2 months ago
Top-k Query Evaluation with Probabilistic Guarantees
Top-k queries based on ranking elements of multidimensional datasets are a fundamental building block for many kinds of information discovery. The best known general-purpose algor...
Martin Theobald, Gerhard Weikum, Ralf Schenkel