Graph-Based Relational Learning with a Polynomial Time Projection Algorithm

Abstract : The paper presents a new projection operator for graphs, named AC- projection, which exhibits good complexity properties as opposed to the graph isomorphism (Θ-subsumption) operator typically used in graph mining. We study the size of the search space and some practical properties of the projection operator. These properties give us a specialization algorithm using simple local operations. Then we prove ex- perimentally that we can achieve an important performance gain (poly- nomial complexity projection) without or with non-significant loss of discovered patterns quality.
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Communication dans un congrès
Stephen Muggleton. ILP'2011: International Conference on Inductive Logic Programming, Jul 2011, Cumberland Lodge, Windsor Great Park, United Kingdom. pp.98-112, 2012, LNAI. 〈http://ilp11.doc.ic.ac.uk/〉
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Dernière modification le : jeudi 11 janvier 2018 - 06:26:23
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Brahim Douar, Michel Liquière, Chiraz Latiri, Yahya Slimani. Graph-Based Relational Learning with a Polynomial Time Projection Algorithm. Stephen Muggleton. ILP'2011: International Conference on Inductive Logic Programming, Jul 2011, Cumberland Lodge, Windsor Great Park, United Kingdom. pp.98-112, 2012, LNAI. 〈http://ilp11.doc.ic.ac.uk/〉. 〈lirmm-00757471〉

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