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Authors: Ikuo Kobayashi, Koichi Furukawa, Tomonobu Ozaki, and Mutsumi Imai
Article title: A Computational Model for Children's Language Acquisition using Inductive Logic Programming
Publ. type: Article
Volume: 6
Article No: 18
Language: English
Abstract [en]: This paper proposes a computational model for children's word acquisition based on inductive logic programming. There are three fundamental features in our approach. Firstly, we incorporate cognitive biases developed recently to explain the efficiency of children's language acquisition. Secondly, we 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 a 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. Thirdly, we pursue resemblance to human brain in functional level.

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.

Publisher: Linköping University Electronic Press
Year: 2001
Available: 2001-08-30 (original publication), 2001-10-31 (revised version)
No. of pages: 13 (original publication), 19 (revised version)
Series: Linköping Electronic Articles in Computer and Information Science
ISSN: 1401-9841

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Last updated: 2017-02-21