Word embedding

Known as: Word vector space, Thought vectors, Word vectors 
Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words… (More)
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BioinformaticsBrown clusteringCo-occurrence matrixDeep learning
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Papers overview

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Highly Cited
2018
Highly Cited
2018
Deep contextualized word representations
We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g… (More)
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Highly Cited
2016
Highly Cited
2016
How to Generate a Good Word Embedding
The authors analyze three critical components in training word embeddings: model, corpus, and training parameters. They… (More)
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Highly Cited
2015
Highly Cited
2015
Improving Distributional Similarity with Lessons Learned from Word Embeddings
Recent trends suggest that neural-network-inspired word embedding models outperform traditional count-based distributional models… (More)
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Highly Cited
2015
Highly Cited
2015
Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation
Word embedding has been found to be highly powerful to translate words from one language to another by a simple linear transform… (More)
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Highly Cited
2014
Highly Cited
2014
Dependency-Based Word Embeddings
While continuous word embeddings are gaining popularity, current models are based solely on linear contexts. In this work, we… (More)
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Highly Cited
2014
Highly Cited
2014
Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification
We present a method that learns word embedding for Twitter sentiment classification in this paper. Most existing algorithms for… (More)
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Highly Cited
2014
Highly Cited
2014
Neural Word Embedding as Implicit Matrix Factorization
We analyze skip-gram with negative-sampling (SGNS), a word embedding method introduced by Mikolov et al., and show that it is… (More)
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Highly Cited
2014
Highly Cited
2014
word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method
The word2vec software of Tomas Mikolov and colleagues 1 has gained a lot of traction lately, and provides state-of-the-art word… (More)
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Highly Cited
2014
Highly Cited
2014
Knowledge-Powered Deep Learning for Word Embedding
The basis of applying deep learning to solve natural language processing tasks is to obtain high-quality distributed… (More)
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Highly Cited
2014
Highly Cited
2014
Glove: Global Vectors for Word Representation
Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic… (More)
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