This book constitutes the refereed proceedings of the 8th International Conference on Inductive Logic Programming, ILP-98, held in Madison, Wisconsin, USA, in July 1998.The 27 revised full papers presented together with the abstracts of three invited talks were carefully reviewed and selected for inclusion in the book. All relevant aspects of inductive logic programming are covered ranging from theory to implementations and applications.
This book constitutes the refereed proceedings of the 8th International Conference on Inductive Logic Programming, ILP-98, held in Madison, Wisconsin, USA, in July 1998.The 27 revised full papers presented together with the abstracts of three invited talks were carefully reviewed and selected for inclusion in the book. All relevant aspects of inductive logic programming are covered ranging from theory to implementations and applications.
Attribute-value learning versus inductive logic programming: The missing links.- Advances in ILP theory and implementations.- Application of ILP to problems in chemistry and biology.- Relational reinforcement learning.- Learning first-order acyclic Horn programs from entailment.- Combining statistical and relational methods for learning in hypertext domains.- Application of inductive logic programming to discover rules governing the three-dimensional topology of protein structure.- Term comparisons in first-order similarity measures.- Stochastic propositionalization of non-determinate background knowledge.- A stochastic simple similarity.- Using prior probabilities and density estimation for relational classification.- Induction of Constraint Grammar-rules using Progol.- A hybrid approach to word segmentation.- Learning multilingual morphology with Clog.- Using ILP-systems for verification and validation of multi-agent systems.- Inducing shogi heuristics using inductive logic programming.- Repeat learning using predicate invention.- Normal programs and multiple predicate learning.- Strongly typed inductive concept learning.- Function-free Horn clauses are hard to approximate.- DOGMA: A GA-based relational learner.- Generalization under implication by ?-subsumption.- Prolog, refinements and RLGG's.- Learning structurally indeterminate clauses.- Completing Inverse Entailment.- Distances and limits on Herbrand interpretations.- Relational distance-based clustering.- A framework for defining distances between first-order logic objects.- Detecting traffic problems with ILP.- A comparison of ILP and propositional systems on propositional traffic data.
Attribute-value learning versus inductive logic programming: The missing links.- Advances in ILP theory and implementations.- Application of ILP to problems in chemistry and biology.- Relational reinforcement learning.- Learning first-order acyclic Horn programs from entailment.- Combining statistical and relational methods for learning in hypertext domains.- Application of inductive logic programming to discover rules governing the three-dimensional topology of protein structure.- Term comparisons in first-order similarity measures.- Stochastic propositionalization of non-determinate background knowledge.- A stochastic simple similarity.- Using prior probabilities and density estimation for relational classification.- Induction of Constraint Grammar-rules using Progol.- A hybrid approach to word segmentation.- Learning multilingual morphology with Clog.- Using ILP-systems for verification and validation of multi-agent systems.- Inducing shogi heuristics using inductive logic programming.- Repeat learning using predicate invention.- Normal programs and multiple predicate learning.- Strongly typed inductive concept learning.- Function-free Horn clauses are hard to approximate.- DOGMA: A GA-based relational learner.- Generalization under implication by ?-subsumption.- Prolog, refinements and RLGG's.- Learning structurally indeterminate clauses.- Completing Inverse Entailment.- Distances and limits on Herbrand interpretations.- Relational distance-based clustering.- A framework for defining distances between first-order logic objects.- Detecting traffic problems with ILP.- A comparison of ILP and propositional systems on propositional traffic data.
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