NDLI: Top-k Query Processing in Uncertain Databases

Content Provider	IEEE Xplore Digital Library
Author	Soliman, M.A. Ilyas, I.F. Chen-Chuan Chang, K.
Copyright Year	2007
Description	Author affiliation: Sch. of Comput. Sci., Waterloo Univ., Ont., Canada (Soliman, M.A.; Ilyas, I.F.)
Abstract	Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between score and uncertainty makes traditional techniques inapplicable. We introduce new probabilistic formulations for top-k queries. Our formulations are based on "marriage" of traditional top-k semantics and possible worlds semantics. In the light of these formulations, we construct a framework that encapsulates a state space model and efficient query processing techniques to tackle the challenges of uncertain data settings. We prove that our techniques are optimal in terms of the number of accessed tuples and materialized search states. Our experiments show the efficiency of our techniques under different data distributions with orders of magnitude improvement over naive materialization of possible worlds.
Starting Page	896
Ending Page	905
File Size	365507
Page Count	10
File Format	PDF
ISBN	1424408024
DOI	10.1109/ICDE.2007.367935
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-15
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Query processing Databases Uncertainty Data models Computer science Radar detection Humans State-space methods Voltage Radar tracking
Content Type	Text
Resource Type	Article

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