research data . Dataset . 2014

Don't count, predict! Semantic vectors

Baroni, Marco; Dinu, Georgiana; Kruszewski, Germán;
Open Access
  • Published: 01 Jun 2014
  • Publisher: Zenodo
Abstract
<p>Semantic vectors associated with the paper &quot;<a href="https://www.aclweb.org/anthology/P14-1023">Don&#39;t count, predict! A systematic comparison of context-counting vs context-predicting semantics vectors</a>&quot;</p> <p><strong>Abstract:</strong> context-predicting models (more commonly known as embeddings or neural language models) are the new kids on the distributional semantics block. Despite the buzz surrounding these models, the literature is still lacking a systematic comparison of the predictive models with classic, count-vector-based distributional semantic approaches. In this paper, we perform such an extensive evaluation, on a wide range of ...
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Funded by
EC| COMPOSES
Project
COMPOSES
Compositional Operations in Semantic Space
  • Funder: European Commission (EC)
  • Project Code: 283554
  • Funding stream: FP7 | SP2 | ERC
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Dataset . 2014
Provider: Zenodo
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Dataset . 2014
Provider: Datacite
Zenodo
Dataset . 2014
Provider: Datacite
Zenodo
Dataset . 2014
Provider: Datacite
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