Inductive Logic Programming: 12th International Conference, ILP 2002, Sydney, Australia, July 9-11, 2002. Revised Papers

by Stan Matwin (Editor)

Contributed Papers.- Propositionalization for Clustering Symbolic Relational Descriptions.- Efficient and Effective Induction of First Order Decision Lists.- Learning with Feature Description Logics.- An Empirical Evaluation of Bagging in Inductive Logic Programming.- Kernels for Structured Data.- Experimental Comparison of Graph-Based Relational Concept Learning with Inductive Logic Programming Systems.- Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners.- Learnability of Description Logic Programs.- 1 A True First-Order Bayesian Classifier.- Relational Subgroup Discovery through First-Order Feature Construction.- Mining Frequent Logical Sequences with SPIRIT-LoG.- Using Theory Completion to Learn a Robot Navigation Control Program.- Learning Structure and Parameters of Stochastic Logic Programs.- A Novel Approach to Machine Genetic Programming and Stochastic Grammars.- Revision of First-Order Bayesian Classifiers.- The Applicability to ILP of Results Concerning the Ordering of Binomial Populations.- Compact Representation of Knowledge Bases in ILP.- A Polynomial Time Matching Algorithm of Structured Ordered Tree Patterns for Data Mining from Semistructured Data.- A Genetic Algorithms Approach to ILP.- Experimental Investigation of Pruning Methods for Relational Pattern Discovery.- Noise-Resistant Incremental Relational Learning Using Possible Worlds.- Lattice-Search Runtime Distributions May Be Heavy-Tailed.- Invited Talk Abstracts.- Learning in Rich Inductive Logic Programming and Computational Scientific Discovery.

368 pages, Paperback

Published March 12, 2014