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Being inspired by the success of \texttt{word2vec} \citep{mikolov2013distributed} in capturing analogies, we study the conjecture that analogical relations can be represented by vector spaces.
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John R Firth. 1957 · 1955
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The structure-mapping engine: Algorithm and examples
Brian Falkenhainer, Kenneth D. Forbus, and Dedre Gentner. 1989 · 1989
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Word association norms, mutual information, and lexicography
Kenneth Ward Church and Patrick Hanks. 1990 · 1990
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The copycat project: a model of mental fluidity and analogy-making
Douglas Richard Hofstadter and Melanie Mitchell. 1995 · 1995
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Corpus-based learning of analogies and semantic relations
Peter D. Turney and Michael L. Littman. 2005 · 2005
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Three new graphical models for statistical language modelling
Andriy Mnih and Geoffrey Hinton. 2007 · 2007
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Metaphors We Live By
George Lakoff and Mark Johnson. 2008 · 2008
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From frequency to meaning: Vector space models of semantics
Peter D Turney and Patrick Pantel. 2010 · 2010
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Don’t count, predict! a systematic comparison of context-counting vs. context-predicting semantic vectors
Marco Baroni, Georgiana Dinu, and Germán Kruszewski. 2014 · 2014
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Linguistic regularities in sparse and explicit word representations
Omer Levy and Yoav Goldberg. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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A latent variable model approach to pmi-based word embeddings
Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, and Andrej Risteski. 2016 · 2016
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