Incorporating constraints in probabilistic XML

Sara Cohen*, Benny Kimelfeld, Yehoshua Sagiv

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Scopus citations

Abstract

Constraints are important not just for maintaining data integrity, but also because they capture natural probabilistic dependencies among data items. A probabilistic XML database (PXDB) is the probability sub-space comprising the instances of a p-document that satisfy a set of constraints. In contrast to existing models that can express probabilistic dependencies, it is shown that query evaluation is tractable in PXDBs. The problems of sampling and determining well-definedness (i.e., whether the above sub-space is nonempty) are also tractable. Furthermore, queries and constraints can include the aggregate functions count, max, rain and ratio. Finally, this approach can be easily extended to allow a probabilistic interpretation of constraints.

Original languageAmerican English
Title of host publicationPODS'08
Subtitle of host publicationProceedings of the 27th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems 2008
Pages109-118
Number of pages10
DOIs
StatePublished - 2008
Event27th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems 2008, PODS'08 - Vancouver, BC, United States
Duration: 9 Jun 200811 Jun 2008

Publication series

NameProceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems

Conference

Conference27th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems 2008, PODS'08
Country/TerritoryUnited States
CityVancouver, BC
Period9/06/0811/06/08

Keywords

  • Constraints
  • Probabilistic XML
  • Probabilistic databases
  • Sampling probabilistic data

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