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On probabilistic fixpoint and Markov chain query languages

Published:06 June 2010Publication History

ABSTRACT

We study highly expressive query languages such as datalog, fixpoint, and while-languages on probabilistic databases. We generalize these languages such that computation steps (e.g. datalog rules) can fire probabilistically. We define two possible semantics for such query languages, namely inflationary semantics where the results of each computation step are added to the current database and noninflationary queries that induce a random walk in-between database instances. We then study the complexity of exact and approximate query evaluation under these semantics.

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            • Published in

              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

              Copyright © 2010 ACM

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 6 June 2010

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