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PageRank, ProPPR, and Stochastic Logic Programs
Department of Computer Science, KU Leuven, Leuven, Belgium.
Department of Computer Science, KU Leuven, Leuven, Belgium.
Department of Computer Science, KU Leuven, Leuven, Belgium.ORCID iD: 0000-0002-6860-6303
2014 (English)In: Inductive Logic Programming: 24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers / [ed] Jesse Davis; Jan Ramon, Springer, 2014, Vol. 9046, p. 168-180Conference paper, Published paper (Refereed)
Abstract [en]

A key feature of ProPPR, a recent probabilistic logic language inspired by stochastic logic programs (SLPs), is its use of personalized PageRank for efficient inference. We adopt this view of probabilistic inference as a random walk over a graph constructed from a labeled logic program to investigate the relationship between these two languages, showing that the differences in semantics rule out direct, generally applicable translations between them.

Place, publisher, year, edition, pages
Springer, 2014. Vol. 9046, p. 168-180
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 9046
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:oru:diva-92414DOI: 10.1007/978-3-319-23708-4_12ISI: 000367791200012Scopus ID: 2-s2.0-84954134153ISBN: 9783319237077 (print)ISBN: 9783319237084 (electronic)OAI: oai:DiVA.org:oru-92414DiVA, id: diva2:1568034
Conference
24th International Conference on Inductive Logic Programming (ILP 2014), Vienna, Austria, July 14-16, 2014
Available from: 2021-06-17 Created: 2021-06-17 Last updated: 2021-06-17Bibliographically approved

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De Raedt, Luc

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