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Induc tive Logic Programming (ILP) is a subfield of mach ine learning, which uses logic programming as a un iform representation technique for examples, backg round knowledge and hypotheses. Due to its strong representation formalism, based on first-order log ic, ILP provides an excellent means for multi-rela tional learning and data mining. The ILP conferenc e series, started in 1991, is the premier internat ional forum for learning from structured relationa l data. Originally focusing on the induction of lo gic programs, over the years it has expanded its r esearch horizon significantly and welcomes contrib utions to all aspects of learning in logic, multi- relational data mining, statistical relational lea rning, graph and tree mining, learning in other (n on-propositional) logic-based knowledge representa tion frameworks, exploring intersections to statis tical learning and other probabilistic approaches. \n

\n \n \nFor more inf ormation, see\n http://ilp16.doc.ic.ac.uk \n

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URL:/NewsandEvents/Archives/2016/newsitem/7493/4-6
-September-2016-The-26th-International-Conference-
on-Inductive-Logic-Programming-ILP-2016-London-Eng
land
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Submissions are still open for short papers and papers relevan t to the \n conference topics that have bee n recently published/accepted for \n public ation by a first-class conference.\nSubmission dea dline: 24 July 2016.\n

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