A computational model for children's language acquisition using inductive logic programming

Ikuo Kobayashi, Koichi Furukawa, Tomonobu Ozaki, Mutsumi Imai

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

This paper describes our research activity on developing a computational model for children's word acquisition using inductive logic programming. We incorporate cognitive biases developed recently to explain the efficiency of children's language acquisition. We also design a co-evolution mechanism of acquiring concept definitions for words and developing concept hierarchy. Concept hierarchy plays an important role of defining contexts for later word learning processes. A context switching mechanism is used to select relevant set of attributes for learning a word depending on the category which it belongs to. On the other hand, during acquiring definitions for words, concept hierarchy is developed. We developed an experimental language acquisition system called WISDOM (Word Induction System for Deriving Object Model) and conducted virtual experiments or simulations on acquisition of words in two different categories. The experiments shows feasibility of our approach.

Original languageEnglish
Title of host publicationProgress in Discovery Science
PublisherSpringer Verlag
Pages140-155
Number of pages16
ISBN (Print)3540433384, 9783540433385
DOIs
Publication statusPublished - 2002 Jan 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2281
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Kobayashi, I., Furukawa, K., Ozaki, T., & Imai, M. (2002). A computational model for children's language acquisition using inductive logic programming. In Progress in Discovery Science (pp. 140-155). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2281). Springer Verlag. https://doi.org/10.1007/3-540-45884-0_7