Literaturnachweis - Detailanzeige
| Autor/in | Vogt, Paul |
|---|---|
| Titel | Exploring the Robustness of Cross-Situational Learning under Zipfian Distributions |
| Quelle | In: Cognitive Science, 36 (2012) 4, S.726-739 (14 Seiten)
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0364-0213 |
| DOI | 10.1111/j.1551-6709.2011.1226.x |
| Schlagwörter | Vocabulary Development; Learning; Mathematical Models; Robustness (Statistics); Statistical Distributions |
| Abstract | Cross-situational learning has recently gained attention as a plausible candidate for the mechanism that underlies the learning of word-meaning mappings. In a recent study, Blythe and colleagues have studied how many trials are theoretically required to learn a human-sized lexicon using cross-situational learning. They show that the level of referential uncertainty exposed to learners could be relatively large. However, one of the assumptions they made in designing their mathematical model is questionable. Although they rightfully assumed that words are distributed according to Zipf's law, they applied a uniform distribution of meanings. In this article, Zipf's law is also applied to the distribution of meanings, and it is shown that under this condition, cross-situational learning can only be plausible when referential uncertainty is sufficiently small. It is concluded that cross-situational learning is a plausible learning mechanism but needs to be guided by heuristics that aid word learners with reducing referential uncertainty. (Contains 1 note and 5 figures.) (As Provided). |
| Anmerkungen | Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA/ |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2017/4/10 |
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