Conference paper Open Access

Character-based Neural Embeddings for Tweet Clustering

Nixon, Lyndon; Vakulenko, Svitlana; Lupu, Mihai


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  <dc:creator>Nixon, Lyndon</dc:creator>
  <dc:creator>Vakulenko, Svitlana</dc:creator>
  <dc:creator>Lupu, Mihai</dc:creator>
  <dc:date>2017-04-03</dc:date>
  <dc:description>In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks. The proposed approach overcomes the limitations related to the vocabulary explosion in the word-based models and allows for the seamless processing of the multilingual content. Our evaluation results and code are available on-line.</dc:description>
  <dc:identifier>https://zenodo.org/record/582565</dc:identifier>
  <dc:identifier>10.5281/zenodo.582565</dc:identifier>
  <dc:identifier>oai:zenodo.org:582565</dc:identifier>
  <dc:relation>url:https://zenodo.org/communities/invid-h2020</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Story Detection, Tweet Clustering, Tweet2vec, Vector Space Model, Character-based Embedding</dc:subject>
  <dc:title>Character-based Neural Embeddings for Tweet Clustering</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
</oai_dc:dc>
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