作者: Fei Xu , Joshua B. Tenenbaum
DOI: 10.1111/J.1467-7687.2007.00590.X
关键词: Sampling (statistics) 、 Psychology 、 Context (language use) 、 Artificial intelligence 、 Associative property 、 Semantics 、 Natural language processing 、 Word (computer architecture) 、 Bayesian inference 、 Bayesian probability 、 Bayesian statistics 、 Statistics
摘要: We report a new study testing our proposal that word learning may be best explained as an approximate form of Bayesian inference (Xu & Tenenbaum, in press). Children are capable …