Aggregates in generalized temporally indeterminate databases

Octavian Udrea*, Zoran Majkić, V. S. Subrahmanian

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Dyreson and Snodgrass as well as Dekhtyar et. al. have provided a probabilistic model (as well as compelling example applications) for why there may be temporal indeterminacy in databases. In this paper, we first propose a formal model for aggregate computation in such databases when there is uncertainty not just in the temporal attribute, but also in the ordinary (non-temporal) attributes. We identify two types of aggregates: event correlated aggregates, and non event correlated aggregations, and provide efficient algorithms for both of them. We prove that our algorithms are correct, and we present experimental results showing that the algorithms work well in practice.

Original languageEnglish (US)
Title of host publicationScalable Uncertainty Management - 1st International Conference, SUM 2007, Proceedings
PublisherSpringer Verlag
Pages171-186
Number of pages16
ISBN (Print)9783540754077
DOIs
StatePublished - 2007
Externally publishedYes
Event1st International Conference on Scalable Uncertainty Management, SUM 2007 - Washington, DC, United States
Duration: Oct 10 2007Oct 12 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4772 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Scalable Uncertainty Management, SUM 2007
Country/TerritoryUnited States
CityWashington, DC
Period10/10/0710/12/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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