Uncertain Top-k Queries
Probabilistic ranking; Probabilistic top-k queries; Uncertain top-k queries
Given a relation R and a scoring function F that assigns a numeric score to each tuple in R, a top-k query returns the k tuples in R with the top ranks according to the scores computed by F. An uncertain top-k query is a top-k query where uncertainty (probabilistic) models are used to describe either R, F, or both R and F. Integrating the semantics of ranking and uncertainty models results in defining a probability distribution on the possible ranks of a given tuple in R according to F. Different formulations of uncertain top-k queries arise from such interplay between scoring and probabilistic measures. Query processing algorithms aim at minimizing the needed score and probabilistic computation by exploiting available data access paths and probabilistic early termination criteria.
Many uncertain/probabilistic data models adopt possible world semantics, where an...
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