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- W2116747026 abstract "Abstract We investigate language-agnostic algorithms for the construction of unsupervised distributional semantic models using web-harvested corpora. Specifically, a corpus is created from web document snippets, and the relevant semantic similarity statistics are encoded in a semantic network. We propose the notion of semantic neighborhoods that are defined using co-occurrence or context similarity features. Three neighborhood-based similarity metrics are proposed, motivated by the hypotheses of attributional and maximum sense similarity. The proposed metrics are evaluated against human similarity ratings achieving state-of-the-art results." @default.
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- W2116747026 date "2013-07-26" @default.
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- W2116747026 title "Similarity computation using semantic networks created from web-harvested data" @default.
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- W2116747026 doi "https://doi.org/10.1017/s1351324913000144" @default.
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