Distributional Models of Word Meaning
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Cites background or methods from "Distributional Models of Word Meani..."
...Excellent reviews in this respect are provided by Sahlgren (2006), Turney and Pantel (2010), Lenci (2008, 2018), Jones et al....
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...Alongside this, we describe how traditional, count-based DSMs2 such as LSA, HAL, or GloVe are typically implemented (for comprehensive overviews, see Lenci, 2018; Turney & Pantel, 2010) and what type of information their word vectors actually represent....
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References
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"Distributional Models of Word Meani..." refers background in this paper
...…al. (2007) High-dimensional explorer (HiDEx) Generalization of HAL with a larger range of parameter settings Shaoul & Westbury (2010) Global vectors (GloVe) Word-by-word matrix reduced with weighted least-squares regression Pennington et al. (2014) Abbreviation: SVD, singular value decomposition....
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"Distributional Models of Word Meani..." refers background or methods in this paper
...Various types of “linguistic regularities” have been claimed to be identifiable by neural embeddings (Mikolov et al. 2013c)....
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...The most popular neural DSM is the one implemented in the word2vec library, which uses the softmax function for predicting b given a (Mikolov et al. 2013a,b): (7) p(b |a) = exp(b · a)∑ b ′∈C exp(b′ · a) , where C is the set of context words and b and a are the vector representations for the context…...
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