Issues in learning language in logic

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

2 Citations (Scopus)

Abstract

Selected issues concerning the use of logical representations in machine learning of natural language are discussed. It is argued that the flexibility and expressivity of logical representations are particularly useful in more complex natural language learning tasks. A number of inductive logic programming (ILP) techniques for natural language are analysed including the CHILL system, abduction and the incorporation of linguistic knowledge, including active learning. Hybrid approaches integrating ILP with manual development environments and probabilistic techniques are advocated.
Original languageEnglish
Title of host publicationComputational Logic
EditorsAntonis C. Kakas, Fariba Sadri
Place of PublicationBerlin
PublisherSpringer-Verlag Berlin
Pages491-505
Number of pages15
ISBN (Electronic)978-3-540-45632-2
ISBN (Print)978-3-540-43960-8
DOIs
Publication statusPublished - 27 Jul 2002

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume2408
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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