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Modeling word perception using the Elman network
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DOI：10.1016/j.neucom.2008.04.030.png)
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摘要
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This paper presents an automatic acquisition process to acquire the semantic meaning for the words. This process obtains the representation vectors for stemmed words by iteratively improving the vectors, using a trained Elman network. Experiments performed on a corpus composed of Shakespeare's writings show its linguistic analysis and categorization abilities. (C) 2008 Elsevier B.V. All rights reserved.
Keyword:
Word perception
Compositional representation
Authorship
Stylistic similarity
Categorization
Semantic search
Elman network
Linguistic analysis
Personalized code
Content addressable memory
Polysemous word
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期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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