research-article

Computing query probability with incidence algebras

Authors:

Karl Schnaitter,

Dan SuciuAuthors Info & Claims

PODS '10: Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems

Pages 203 - 214

https://doi.org/10.1145/1807085.1807113

Published: 06 June 2010 Publication History

Abstract

We describe an algorithm that evaluates queries over probabilistic databases using Mobius' inversion formula in incidence algebras. The queries we consider are unions of conjunctive queries (equivalently: existential, positive First Order sentences), and the probabilistic databases are tuple-independent structures. Our algorithm runs in PTIME on a subset of queries called "safe" queries, and is complete, in the sense that every unsafe query is hard for the class FP^#P. The algorithm is very simple and easy to implement in practice, yet it is non-obvious. Mobius' inversion formula, which is in essence inclusion-exclusion, plays a key role for completeness, by allowing the algorithm to compute the probability of some safe queries even when they have some subqueries that are unsafe. We also apply the same lattice-theoretic techniques to analyze an algorithm based on lifted conditioning, and prove that it is incomplete.

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Cited By

van Bremen TMeel KGeerts FNgo HSintos S(2023)Probabilistic Query Evaluation: The Combined FPRAS LandscapeProceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3584372.3588677(339-347)Online publication date: 18-Jun-2023
Suciu DOlteanu DRé CKoch C(2022)Probabilistic DatabasesundefinedOnline publication date: 2-Mar-2022
Khanna SRoy STannen V(2020)Queries with difference on probabilistic databasesProceedings of the VLDB Endowment10.14778/3402707.34027414:11(1051-1062)Online publication date: 3-Jun-2020
Show More Cited By

Index Terms

Computing query probability with incidence algebras
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
2. Theory of computation

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cover image ACM Conferences

PODS '10: Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems

June 2010

350 pages

ISBN:9781450300339

DOI:10.1145/1807085

General Chair:
Jan Paredaens
University of Antwerp, Belgium
,
Program Chair:
Dirk Van Gucht
Indiana University, USA

Copyright © 2010 ACM.

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Published: 06 June 2010

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SIGMOD/PODS '10: International Conference on Management of Data

June 6 - 11, 2010

Indiana, Indianapolis, USA

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PODS '10 Paper Acceptance Rate 27 of 113 submissions, 24%;

Overall Acceptance Rate 642 of 2,707 submissions, 24%

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Cited By

van Bremen TMeel KGeerts FNgo HSintos S(2023)Probabilistic Query Evaluation: The Combined FPRAS LandscapeProceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3584372.3588677(339-347)Online publication date: 18-Jun-2023
Suciu DOlteanu DRé CKoch C(2022)Probabilistic DatabasesundefinedOnline publication date: 2-Mar-2022
Khanna SRoy STannen V(2020)Queries with difference on probabilistic databasesProceedings of the VLDB Endowment10.14778/3402707.34027414:11(1051-1062)Online publication date: 3-Jun-2020
Gupta RSharma SRoy SMeel K(2019): Weighted and Projected SamplingTools and Algorithms for the Construction and Analysis of Systems10.1007/978-3-030-17462-0_4(59-76)Online publication date: 6-Apr-2019
Lüdtke SSchröder MKrüger FBader SKirste T(2018)State-space abstractions for probabilistic inferenceJournal of Artificial Intelligence Research10.1613/jair.1.1126163:1(789-848)Online publication date: 1-Sep-2018
Winslett MBraganholo V(2018)Dan Suciu Speaks Out on Research, Shyness and Being a ScientistACM SIGMOD Record10.1145/3186549.318655746:4(28-34)Online publication date: 22-Feb-2018
Amarilli ABourhis PSenellart PMilo TTan W(2016)Tractable Lineages on Treelike InstancesProceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/2902251.2902301(355-370)Online publication date: 15-Jun-2016
Gatterbauer WSuciu D(2014)Oblivious bounds on the probability of boolean functionsACM Transactions on Database Systems10.1145/253264139:1(1-34)Online publication date: 6-Jan-2014
Dylla MTheobald MMiliaraki I(2014)Querying and Learning in Probabilistic DatabasesReasoning Web. Reasoning on the Web in the Big Data Era10.1007/978-3-319-10587-1_8(313-368)Online publication date: 2014
Roy SChiticariu LFeldman VReiss FZhu HRoss KSrivastava DPapadias D(2013)Provenance-based dictionary refinement in information extractionProceedings of the 2013 ACM SIGMOD International Conference on Management of Data10.1145/2463676.2465284(457-468)Online publication date: 22-Jun-2013
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