Incorporating constraints in probabilistic XML

Sara Cohen*, Benny Kimelfeld, Yehoshua Sagiv

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Constraints are important, not only for maintaining data integrity, but also because they capture natural probabilistic dependencies among data items. A probabilistic XML database (PXDB) is the probability subspace 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 aforesaid subspace is nonempty) are also tractable. Furthermore, queries and constraints can include the aggregate functions count, max, min, and ratio. Finally, this approach can be easily extended to allow a probabilistic interpretation of constraints.

Original languageAmerican English
Article number18
JournalACM Transactions on Database Systems
Volume34
Issue number3
DOIs
StatePublished - 1 Aug 2009

Keywords

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

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