Dataset Open Access

Word Embedding of Amazon Product Review Corpus

Marc Schulder; Wiegand, Michael


Dublin Core Export

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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Marc Schulder</dc:creator>
  <dc:creator>Wiegand, Michael</dc:creator>
  <dc:date>2017-11-27</dc:date>
  <dc:description>A word embedding of the Amazon Product Review Corpus (Jindal and Liu, 2008).

Created using Word2Vec in CBOW mode, 500 dimensions and window size 5.

Words have been lemmatised and particle verbs have been merged into a single token (e.g. calm_down).




 

Attribution

This dataset was created as part of the following publication:

Marc Schulder, Michael Wiegand, Josef Ruppenhofer and Benjamin Roth (2017). "Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features". Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan, November 27 - December 3, 2017. DOI: 10.5281/zenodo.3365609.

If you use the data in your research or work, please cite the publication.</dc:description>
  <dc:identifier>https://zenodo.org/record/3370051</dc:identifier>
  <dc:identifier>10.5281/zenodo.3370051</dc:identifier>
  <dc:identifier>oai:zenodo.org:3370051</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>doi:10.5281/zenodo.3365609</dc:relation>
  <dc:relation>doi:10.5281/zenodo.3370050</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/natural-language-processing</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Word Embedding</dc:subject>
  <dc:subject>Product Reviews</dc:subject>
  <dc:title>Word Embedding of Amazon Product Review Corpus</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
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