Using Inductive Logic Programming for Natural Language Processing

James Cussens, W. Daelemans

Research output: Other contribution

Abstract

We summarise recent work on using Inductive Logic Programming (ILP) for Natural Language Processing (NLP). ILP performs learning in a first-order logical setting, and is thus well-suited to induce over the various structured representations used in NLP. We present Stochastic Logic Programs (SLPs) and demonstrate their use in ILP when learning from positive examples only. We also give accounts of work on learning grammars from children's books and part-of-speech tagging.
Original languageEnglish
PublisherUniversity of Economics, Prague
Number of pages10
Place of PublicationPrague
Publication statusPublished - 1997

Bibliographical note

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