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» ProUD: Probabilistic Ranking in Uncertain Databases
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ECIR
2003
Springer
13 years 6 months ago
From Uncertain Inference to Probability of Relevance for Advanced IR Applications
Uncertain inference is a probabilistic generalisation of the logical view on databases, ranking documents according to their probabilities that they logically imply the query. For ...
Henrik Nottelmann, Norbert Fuhr
SIGMOD
2009
ACM
175views Database» more  SIGMOD 2009»
14 years 5 months ago
Ranking distributed probabilistic data
Ranking queries are essential tools to process large amounts of probabilistic data that encode exponentially many possible deterministic instances. In many applications where unce...
Feifei Li, Ke Yi, Jeffrey Jestes
SIGMOD
2010
ACM
153views Database» more  SIGMOD 2010»
13 years 10 months ago
Threshold query optimization for uncertain data
The probabilistic threshold query (PTQ) is one of the most common queries in uncertain databases, where all results satisfying the query with probabilities that meet the threshold...
Yinian Qi, Rohit Jain, Sarvjeet Singh, Sunil Prabh...
SIGMOD
2008
ACM
164views Database» more  SIGMOD 2008»
14 years 5 months ago
Finding frequent items in probabilistic data
Computing statistical information on probabilistic data has attracted a lot of attention recently, as the data generated from a wide range of data sources are inherently fuzzy or ...
Qin Zhang, Feifei Li, Ke Yi
SSD
2007
Springer
124views Database» more  SSD 2007»
13 years 11 months ago
Querying Objects Modeled by Arbitrary Probability Distributions
In many modern applications such as biometric identification systems, sensor networks, medical imaging, geology, and multimedia databases, the data objects are not described exact...
Christian Böhm, Peter Kunath, Alexey Pryakhin...