Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data 2011
DOI: 10.1145/1989323.1989409
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Querying uncertain data with aggregate constraints

Abstract: Data uncertainty arises in many situations. A common approach to query processing uncertain data is to sample many "possible worlds" from the uncertain data and to run queries against the possible worlds. However, sampling is not a trivial task, as a randomly sampled possible world may not satisfy known constraints imposed on the data. In this paper, we focus on an important category of constraints, the aggregate constraints. An aggregate constraint is placed on a set of records instead of on a single record, … Show more

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Cited by 12 publications
(9 citation statements)
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References 26 publications
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“…Moreover, they do not offer solutions which do not require exponential enumeration of all possibilities. Other systems support efficient implementations of Monte Carlo methods [9], [12], but empirically we show that such sampling does not explore the full range of possibilities. Thus, these approaches do not provide correct answers for queries such as those described in Examples 1 and 2.…”
Section: Related Workmentioning
confidence: 97%
See 1 more Smart Citation
“…Moreover, they do not offer solutions which do not require exponential enumeration of all possibilities. Other systems support efficient implementations of Monte Carlo methods [9], [12], but empirically we show that such sampling does not explore the full range of possibilities. Thus, these approaches do not provide correct answers for queries such as those described in Examples 1 and 2.…”
Section: Related Workmentioning
confidence: 97%
“…Recent work in parallel to this [12] discusses sampling only those possible worlds which satisfy some global aggregate constraints. While ostensibly similar, the problem differs from ours since uncertainty is only over tuple values, and techniques provide a sampling mechanism, not a data model.…”
Section: Related Workmentioning
confidence: 99%
“…Finally, in [28], the authors study the problem of constrained sampling. However, the underlying distribution they consider is discrete, whereas we use Gaussian mixtures.…”
Section: Related Workmentioning
confidence: 99%
“…В годы начала космической эры во никла потребност в исследовании поведени идкости в услови х невесомости. К и учени данной проблематики ( адачи определени форм равновеси , условий устойчивости, описани тепловой конвекции, Таврический вестник информатики и математики , 1 (46)' 2020 проблемы малых дви ений) был привлечен отдел прикладной математики. Подобными адачами чут по е стали анимат с в Вычислител ном центре АН СССР (г. Москва) и в Институте математики НАН Украины (г. Киев).…”
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“…а период почти 60-летней научной де тел ности Николай Дмитриевич c соавторами написал более 250 научных работ, более 15 учебных пособий, и дал 8 монографий (полный список трудов доступен на сайте http://nikolay-d-kopachevsky.com). Он вл етс аслу енным де телем науки и техники Украины и России, лауреатом государственной премии Украины 2013 года (в составе авторского коллектива) а Таврический вестник информатики и математики , 1 (46)' 2020 цикл научных работ по гидромеханике акономерности волно-вихревых процессов в сплошной среде , лауреатом премий имени В. И. Вернадского и кавалером Ордена а аслуги 3-й степени. Неоцениму поддер ку в и ни и работе Никола Дмитриевичу ока ывала его ена, с которой он про ил много лет в л бви и согласии.…”
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