Invited Papers / I: |
Probabilistic Relational Models / D. Koller |
Inductive Databases (Abstract) / H. Mannila |
Some Elements of Machine Learning (Extended Abstract) / J.R. Quinlan |
Contributed Papers / II: |
Refinement Operators Can Be (Weakly) Perfect / L. Badea ; M. Stanciu |
Combining Divide-and-Conquer and Separate-and-Conquer for Efficient and Effective Rule Induction / H. Boström ; L. Asker |
Refining Complete Hypotheses in ILP / I. Bratko |
Acquiring Graphic Design Knowledge with Nonmonotonic Inductive Learning / K. Chiba ; H. Ohwada ; F. Mizoguchi |
Morphosyntactic Tagging of Slovene Using Progol / J. Cussens ; S. D&zbreve;eroski ; T. Erjavec |
Experiments in Predicting Biodegradability / S. Dzeroski ; H. Blockeel ; B. Kompare ; S. Kramer ; B. Pfahringer ; W. Van Laer |
1BC: A First-Order Bayesian Classifier / P. Flach ; N. Lachiche |
Sorted Downward Refinement: Building Background Knowledge into a Refinement Operator for Inductive Logic Programming / A.M. Frisch |
A Strong Complete Schema for Inductive Functional Logic Programming / J. Hernández-Orallo ; M.J. Ramírez-Quintana |
Application of Different Learning Methods to Hungarian Part-of-Speech Tagging / T. Horváth ; Z. Alexin ; T. Gyimóthy ; S. Wrobel |
Combining LAPIS and WordNet for the Learning of LR Parsers with Optimal Semantic Constraints / D. Kazakov |
Learning Word Segmentation Rules for Tag Prediction / S. Manandhar |
Approximate ILP Rules by Backpropagation Neural Network: A Result on Thai Character Recognition / B. Kijsirikul ; S. Sinthupinyo |
Rule Evaluation Measures: A Unifying View / N. Lavrač ; B. Zupan |
Improving Part-of-Speech Disambiguation Rules by Adding Linguistic Knowledge / N. Lindberg ; M. Eineborg |
On Sufficient Conditions for Learnability of Logic Programs from Positive Data / E. Martin ; A. Sharma |
A Bounded Search Space of Clausal Theories / H. Midelfart |
Discovering New Knowledge from Graph Data Using Inductive Logic Programming / T. Miyahara ; T. Shoudai ; T. Uchida ; T. Kuboyama ; K. Takahashi ; H. Ueda |
Analogical Prediction / S. Muggleton ; M. Bain |
Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms / S.-H. Nienhuys-Cheng ; J. Ramon ; L. De Raedt |
Theory Recovery / R. Parson ; K. Khan |
Instance Based Function Learning |
Some Properties of Inverse Resolution in Normal Logic Programs / C. Sakama |
An Assessment of ILP-Assisted Models for Toxicology and the PTE-3 Experiment / A. Srinivasan ; R.D. King ; D.W. Bristol |
Author Index |
Invited Papers / I: |
Probabilistic Relational Models / D. Koller |
Inductive Databases (Abstract) / H. Mannila |
Some Elements of Machine Learning (Extended Abstract) / J.R. Quinlan |
Contributed Papers / II: |
Refinement Operators Can Be (Weakly) Perfect / L. Badea ; M. Stanciu |