DocumentCode
480622
Title
Word Learning Using a Self-Organizing Map
Author
Li, Lishu ; Chen, Qinghua ; Cui, Jiaxin ; Fang, Fukang
Author_Institution
Dept. of Syst. Sci., Beijing Normal Univ., Beijing
Volume
2
fYear
2008
fDate
20-22 Dec. 2008
Firstpage
336
Lastpage
340
Abstract
SOMs have been successfully applied in various fields. In this paper, we proposed an expanded SOM model for word learning which is a classic problem in cognitive science. In spite of simple computation of this model, the simulation results are consistent with the conclusion of the newest Bayesian model in the same learning cases. It implies that this model has the ability like human to properly response to different number and span of samples.
Keywords
Bayes methods; data analysis; learning (artificial intelligence); self-organising feature maps; Bayesian model; cognitive science; self-organizing map model; word learning; word-to-meaning mapping; Artificial neural networks; Bayesian methods; Chemical analysis; Cognition; Computational modeling; Humans; Information technology; Neurons; Technology management; Unsupervised learning; SOM; artificial neural networks; word learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-0-7695-3497-8
Type
conf
DOI
10.1109/IITA.2008.65
Filename
4739782
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