Inductive Logic Programming 9th International Workshop, ILP-99, Bled, Slovenia, June 24-27, 1999, Proceedings /

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Dzeroski, Saso (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Flach, Peter A. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1999.
Έκδοση:1st ed. 1999.
Σειρά:Lecture Notes in Artificial Intelligence ; 1634
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • I Invited Papers
  • Probabilistic Relational Models
  • Inductive Databases
  • Some Elements of Machine Learning
  • II Contributed Papers
  • Refinement Operators Can Be (Weakly) Perfect
  • Combining Divide-and-Conquer and Separate-and-Conquer for Efficient and Effective Rule Induction
  • Refining Complete Hypotheses in ILP
  • Acquiring Graphic Design Knowledge with Nonmonotonic Inductive Learning
  • Morphosyntactic Tagging of Slovene Using Progol
  • Experiments in Predicting Biodegradability
  • 1BC: A First-Order Bayesian Classifier
  • Sorted Downward Refinement: Building Background Knowledge into a Refinement Operator for Inductive Logic Programming
  • A Strong Complete Schema for Inductive Functional Logic Programming
  • Application of Different Learning Methods to Hungarian Part-of-Speech Tagging
  • Combining LAPIS and WordNet for the Learning of LR Parsers with Optimal Semantic Constraints
  • Learning Word Segmentation Rules for Tag Prediction
  • Approximate ILP Rules by Backpropagation Neural Network: A Result on Thai Character Recognition
  • Rule Evaluation Measures: A Unifying View
  • Improving Part of Speech Disambiguation Rules by Adding Linguistic Knowledge
  • On Sufficient Conditions for Learnability of Logic Programs from Positive Data
  • A Bounded Search Space of Clausal Theories
  • Discovering New Knowledge from Graph Data Using Inductive Logic Programming
  • Analogical Prediction
  • Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms
  • Theory Recovery
  • Instance based function learning
  • Some Properties of Inverse Resolution in Normal Logic Programs
  • An Assessment of ILP-assisted models for toxicology and the PTE-3 experiment.