A simple computational model for classifying small string sets

Yoshihiko Suhara, Akito Sakurai

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Recent research hypothesizes that the capacity for syntactic recursions forms the computational core of a uniquely human language faculty. Contrary to this hypothesis, Gentner et al. claimed that the capacity to classify sequences from recursive, center-embedded grammar is not uniquely human. We show in this paper that the patterns Gentner used are classified by a Bayesian classifier, a simple and fundamental classifier in machine learning, and consequently we claim that their argument is flawed.

Original languageEnglish
Pages (from-to)270-273
Number of pages4
JournalInternational Congress Series
Volume1301
DOIs
Publication statusPublished - 2007 Jul

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Language
Research
Machine Learning

Keywords

  • Bayesian classification
  • Cognitive language
  • Grammar learning

ASJC Scopus subject areas

  • Medicine(all)

Cite this

A simple computational model for classifying small string sets. / Suhara, Yoshihiko; Sakurai, Akito.

In: International Congress Series, Vol. 1301, 07.2007, p. 270-273.

Research output: Contribution to journalArticle

Suhara, Yoshihiko ; Sakurai, Akito. / A simple computational model for classifying small string sets. In: International Congress Series. 2007 ; Vol. 1301. pp. 270-273.
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