Inductive Logic Programming: 7th International Workshop, ILP-97, Prague, Czech Republic, September 17-20, 1997, Proceedings

ISBN-13: 9783540635147 / Angielski / Miękka / 1997 / 318 str.

Nada Lavrač;Saso Dzeroski

Opis

This book constitutes the refereed proceedings of the 7th International Workshop on Inductive Logic Programming, ILP-97, held in Prague, Czech Republic, in September 1997.
The volume presents revised versions of nine papers in long version and 17 short papers accepted after a thorough reviewing process. Also included are three invited papers by Usama Fayyad, Jean-Francois Puget, and Georg Gottlob. Among the topics addressed are various logic programming issues, natural language processing, speech processing, abductive learning, data mining, knowledge discovery, and relational database systems.

Spis treści

Knowledge discovery in databases: An overview.- On the complexity of some Inductive Logic Programming problems.- Inductive logic programming and constraint logic programming (abstract).- Learning phonetic rules in a speech recognition system.- Cautious induction in inductive logic programming.- Generating numerical literals during refinement.- Lookahead and discretization in ILP.- Data mining via ILP: The application of Progol to a database of enantioseparations.- Part-of-speech tagging using Progol.- Maximum Entropy modeling with Clausal Constraints.- Mining association rules in multiple relations.- Using logical decision trees for clustering.- Induction of Slovene nominal paradigms.- Normal forms for inductive logic programming.- On a sufficient condition for the existence of most specific hypothesis in progol.- Induction of logic programs with more than one recursive clause by analyzing saturations.- A logical framework for graph theoretical decision tree learning.- Learning with abduction.- Systematic Predicate Invention in Inductive Logic Programming.- Learning programs in the event calculus.- Distance between Herbrand interpretations: A measure for approximations to a target concept.- Realizing Progol by forward reasoning.- Probabilistic first-order classification.- Learning Horn definitions with equivalence and membership queries.- Using abstraction schemata in inductive logic programming.- Distance induction in first order logic.- Carcinogenesis predictions using ILP.- Discovery of first-order regularities in a relational database using ofine candidate determination.- Which hypotheses can be found with inverse entailment?.

O autorze

Prof. Dr. Nada Lavrac heads the Department of Knowledge Technologies at the Jo ef Stefan Institute in Ljubljana. She is the author and editor of several books and proceedings in the field of data mining and machine learning, and she has chaired or served on the boards of the main related journals and conferences. Her research interests include machine learning, data mining, and inductive logic programming, and related applications in medicine, public health, bioinformatics, and the management of virtual enterprises. In 1997 she was awarded the Ambassador of Science of Slovenia prize, and in 2007 she was elected as an ECCAI Fellow.