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By representing words with probability densities rather than point vectors, probabilistic word embeddings can capture rich and interpretable semantic information and uncertainty.
On measures of entropy and information
Alfred Renyi · 1961
Earlier work this paper cites.
Convex Statistical Distances
Friedrich Liese and Igor Vajda · 1987
Earlier work this paper cites.
Wordnet: A lexical database for english
George A. Miller · 1995
Earlier work this paper cites.
Nltk: The natural language toolkit
Edward Loper and Steven Bird · 2002
Earlier work this paper cites.
Probability product kernels
Tony Jebara, Risi Kondor, and Andrew Howard · 2004
Earlier work this paper cites.
Characterising measures of lexical distributional similarity
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Earlier work this paper cites.
UKWAC: building the uk’s first public web archive
Steve Bailey and Dave Thompson · 2006
Earlier work this paper cites.
Statistical Inference Based on Divergence Measures , chapter 1, pp. 1–54
Leandro Pardo · 2006
Earlier work this paper cites.
The wacky wide web: a collection of very large linguistically processed web-crawled corpora
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Earlier work this paper cites.
How we blessed distributional semantic evaluation
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Earlier work this paper cites.
Entailment above the word level in distributional semantics
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Earlier work this paper cites.
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