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This paper presents a query evaluation technique for positive relational algebra queries with aggregates on a representation system for probabilistic data based on the algebraic structures of semiring and semimodule. The core of our evaluation technique is a procedure that compiles semimodule and semiring expressions into so-called decomposition trees, for… (More)

- John M O 'hara, James C Higgins, William S Brown, Robert Fink
- 2008

manuscript for publication acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. DISCLAIMER This report was prepared as an account of work sponsored by an agency of the… (More)

This paper investigates the problem of approximating conjunctive queries without self-joins on probabilistic databases by lower and upper bounds that can be computed more efficiently. We study this problem via an indirection: Given a propositional formula &phis;, find formulas in a more restricted language that are greatest lower bound and least upper… (More)

This article describes an approximation algorithm for computing the probability of propositional formulas over discrete random variables. It incrementally refines lower and upper bounds on the probability of the formulas until the desired absolute or relative error guarantee is reached. This algorithm is used by the SPROUT query engine to approximate the… (More)

This paper introduces ENFrame, a unified data processing platform for querying and mining probabilistic data. Using ENFrame, users can write programs in a fragment of Python with constructs such as bounded-range loops, list comprehension, aggregate operations on lists, and calls to external database engines. The program is then interpreted probabilistically… (More)

This paper shows that any non-repeating conjunctive relational query with negation has either polynomial time or #P-hard data complexity on tuple-independent probabilistic databases. This result extends a dichotomy by Dalvi and Suciu for non-repeating conjunctive queries to queries with negation. The tractable queries with negation are precisely the… (More)

This article charts the tractability frontier of two classes of relational algebra queries in tuple-independent probabilistic databases. The first class consists of queries with join, projection, selection, and negation but without repeating relation symbols and union. The second class consists of quantified queries that express the following binary… (More)