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Abstract: The past few years have seen a surge of interest in the field ofprobabilistic logic learning and statistical relational learning. In thisendeavor, many probabilistic logics have been developed. ProbLog is a recentprobabilistic extension of Prolog motivated by the mining of large biologicalnetworks. In ProbLog, facts can be labeled with probabilities. These facts aretreated as mutually independent random variables that indicate whether thesefacts belong to a randomly sampled program. Different kinds of queries can beposed to ProbLog programs. We introduce algorithms that allow the efficientexecution of these queries, discuss their implementation on top of theYAP-Prolog system, and evaluate their performance in the context of largenetworks of biological entities.



Author: Angelika Kimmig, Bart Demoen, Luc De Raedt, VĂ­tor Santos Costa, Ricardo Rocha

Source: https://arxiv.org/



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