• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

DMCA

Dissociation and Propagation for Efficient Query Evaluation over Probabilistic Databases (2010)

Cached

  • Download as a PDF

Download Links

  • [www.cs.washington.edu]
  • [www.cs.washington.edu]
  • [www.cs.washington.edu]
  • [www.cs.washington.edu]
  • [www.andrew.cmu.edu]
  • [www.cs.washington.edu]
  • [www.cs.washington.edu]
  • [homes.cs.washington.edu]
  • [homes.cs.washington.edu]
  • [ewi1276.ewi.utwente.nl:3000]
  • [arxiv.org]

  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Wolfgang Gatterbauer , Abhay K. Jha , Dan Suciu
Citations:10 - 7 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Gatterbauer10dissociationand,
    author = {Wolfgang Gatterbauer and Abhay K. Jha and Dan Suciu},
    title = {Dissociation and Propagation for Efficient Query Evaluation over Probabilistic Databases},
    year = {2010}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

Queries over probabilistic databases are either safe, in which case they can be evaluated entirely in a relational database engine, or unsafe, in which case they need to be evaluated with a general-purpose inference engine at a high cost. This paper proposes a new approach by which every query is evaluated like a safe query inside the database engine, by using a new method called dissociation. A dissociated query is obtained by adding extraneous variables to some atoms until the query becomes safe. We show that the probability of the original query and that of the dissociated query correspond to two well-known scoring functions on graphs, namely graph reliability (which is #P-hard), and the propagation score (which is related to PageRank and is in PTIME): When restricted to graphs, standard query probability is graph reliability, while the dissociated probability is the propagation score. We define a propagation score for conjunctive queries without self-joins and prove (i) that it is is always an upper bound for query reliability, and (ii) that both scores coincide for all safe queries. Given the widespread and successful use of graph propagation methods in practice, we argue for the dissociation method as a good and efficient way to rank probabilistic query results, especially for those queries which are highly intractable for exact probabilistic inference.

Keyphrases

probabilistic database    propagation score    efficient query evaluation    graph reliability    safe query    standard query probability    new method    exact probabilistic inference    probabilistic query result    new approach    efficient way    original query    dissociated query correspond    dissociation method    conjunctive query    upper bound    dissociated probability    successful use    relational database engine    database engine    dissociated query    query reliability    general-purpose inference engine    extraneous variable    graph propagation method    high cost   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University