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Word2vec

Word2vec is a group of related models that are used to produce word embeddings. These models are shallow, two-layer neural networks that are trained… Expand
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Papers overview

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Review
2017
Review
2017
Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT… Expand
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Highly Cited
2016
Highly Cited
2016
The vector representations of fixed dimensionality for words (in text) offered by Word2Vec have been shown to be very useful in… Expand
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Highly Cited
2015
Highly Cited
2015
We present two simple modifications to the models in the popular Word2Vec tool, in order to generate embeddings more suited to… Expand
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Highly Cited
2015
Highly Cited
2015
We achieve similar features clustering using word2vec.A method for sentiment classification based on word2vec and SVMperf is… Expand
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Highly Cited
2015
Highly Cited
2015
In this paper we explore how word vectors built using word2vec can be used to improve the performance of a classifier during… Expand
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Highly Cited
2015
Highly Cited
2015
With the rapid expansion of new available information presented to us online on a daily basis, text classification becomes… Expand
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2015
2015
Big data is a broad data set that has been used in many fields. To process huge data set is a time consuming work, not only due… Expand
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Highly Cited
2014
Highly Cited
2014
The word2vec software of Tomas Mikolov and colleagues (this https URL ) has gained a lot of traction lately, and provides state… Expand
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Review
2014
Review
2014
The word2vec model and application by Mikolov et al. have attracted a great amount of attention in recent two years. The vector… Expand
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2014
2014
We extend the word2vec framework to capture meaning across languages. The input consists of a source text and a word-aligned… Expand
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