@inproceedings{f769ae3f8f534ae3b28470d9231a75d6,
title = "URank: Formulation and efficient evaluation of top-k queries in uncertain databases",
abstract = "Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between query scores and data uncertainty makes traditional techniques inapplicable. We introduce URank, a system that processes new probabilistic formulations of top-k queries inuncertain databases. The new formulations are based on marriage of traditional top-k semantics with possible worlds semantics. URank encapsulates a new processing framework that leverages existing query processing capabilities, and implements efficient search strategies that integrate ranking on scores with ranking on probabilities, to obtain meaningful answers for top-k queries.",
keywords = "Probabilistic data, Query processing, Ranking, Topk, Uncertain data",
author = "Soliman, {Mohamed A.} and Ilyas, {Ihab F.} and Chang, {Kevin Chen Chuan}",
year = "2007",
doi = "10.1145/1247480.1247613",
language = "English (US)",
isbn = "1595936866",
series = "Proceedings of the ACM SIGMOD International Conference on Management of Data",
pages = "1082--1084",
booktitle = "SIGMOD 2007",
note = "SIGMOD 2007: ACM SIGMOD International Conference on Management of Data ; Conference date: 12-06-2007 Through 14-06-2007",
}