Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/53031
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dc.creatorAngelika Kimmig
dc.creatorBart Demoen
dc.creatorLuc De Raedt
dc.creatorVitor Costa
dc.creatorRicardo Rocha
dc.date.accessioned2019-02-06T20:32:55Z-
dc.date.available2019-02-06T20:32:55Z-
dc.date.issued2010
dc.identifier.issn1471-0684
dc.identifier.othersigarra:48914
dc.identifier.urihttps://repositorio-aberto.up.pt/handle/10216/53031-
dc.description.abstractThe past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have been developed. ProbLog is a recent probabilistic extension of Prolog motivated by the mining of large biological networks. In ProbLog, facts can be labeled with probabilities. These facts are treated as mutually independent random variables that indicate whether these facts belong to a randomly sampled program. Different kinds of queries can be posed to ProbLog programs. We introduce algorithms that allow the efficient execution of these queries, discuss their implementation on top of the YAP-Prolog system, and evaluate their performance in the context of large networks of biological entities.
dc.language.isoeng
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectProgramação, Ciências da computação e da informação
dc.subjectProgramming, Computer and information sciences
dc.titleOn the Implementation of the Probabilistic Logic Programming Language ProbLog
dc.typeArtigo em Revista Científica Internacional
dc.contributor.uportoFaculdade de Ciências
dc.subject.fosCiências exactas e naturais::Ciências da computação e da informação
dc.subject.fosNatural sciences::Computer and information sciences
Appears in Collections:FCUP - Artigo em Revista Científica Internacional

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