Learning Language in Logic

This volume has its origins in the ?rst Learning Language in Logic (LLL) wo- shop which took place on 30 June 1999 in Bled, Slovenia immediately after the Ninth International Workshop on Inductive Logic Programming (ILP'99) and the Sixteenth International Conference on Machine Learning (ICML�...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Cussens, James (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Dzeroski, Saso (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2000.
Έκδοση:1st ed. 2000.
Σειρά:Lecture Notes in Artificial Intelligence ; 1925
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introductions & Overviews
  • An Introduction to Inductive Logic Programming and Learning Language in Logic
  • A Brief Introduction to Natural Language Processing for Non-linguists
  • A Closer Look at the Automatic Induction of Linguistic Knowledge
  • Learning for Semantic Interpretation: Scaling Up without Dumbing Down
  • Morphology & Phonology
  • Learning to Lemmatise Slovene Words
  • Achievements and Prospects of Learning Word Morphology with Inductive Logic Programming
  • Learning the Logic of Simple Phonotactics
  • Syntax
  • Grammar Induction as Substructural Inductive Logic Programming
  • Experiments in Inductive Chart Parsing
  • ILP in Part-of-Speech Tagging - An Overview
  • Iterative Part-of-Speech Tagging
  • DCG Induction Using MDL and Parsed Corpora
  • Learning Log-Linear Models on Constraint-Based Grammars for Disambiguation
  • Unsupervised Lexical Learning with Categorial Grammars Using the LLL Corpus
  • Induction of Recursive Transfer Rules
  • Learning for Text Categorization and Information Extraction with ILP
  • Corpus-Based Learning of Semantic Relations by the ILP System, Asium
  • Improving Learning by Choosing Examples Intelligently in Two Natural Language Tasks.