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Short‐text feature expansion and classification based on nonnegative matrix factorization

Zhang, Ling; Jiang, Wenchao; Zhao, Zhiming


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{
  "description": "<p>In this paper, a non\u2010negative matrix factorization feature</p>\n\n<p>expansion (NMFFE) approach was proposed to</p>\n\n<p>overcome the feature\u2010sparsity issue when expanding</p>\n\n<p>features of short\u2010text. First, we took the internal relationships</p>\n\n<p>of short texts and words into account when</p>\n\n<p>segmenting words from texts and constructing their</p>\n\n<p>relationship matrix. Second, we utilized the Dual</p>\n\n<p>regularization non\u2010negative matrix tri\u2010factorization</p>\n\n<p>(DNMTF) algorithm to obtain the words clustering</p>\n\n<p>indicator matrix, which was used to get the feature</p>\n\n<p>space by dimensionality reduction methods. Thirdly,</p>\n\n<p>words with close relationship were selected out from</p>\n\n<p>the feature space and added into the short\u2010text to solve</p>\n\n<p>the sparsity issue. The experimental results showed</p>\n\n<p>that the accuracy of short text classification of our</p>\n\n<p>NMFFE algorithm increased 25.77%, 10.89%, and 1.79%</p>\n\n<p>on three data sets: Web snippets, Twitter sports, and</p>\n\n<p>AGnews, respectively compared with the Word2Vec</p>\n\n<p>algorithm and Char\u2010CNN algorithm. It indicated that</p>\n\n<p>the NMFFE algorithm was better than the BOW algorithm</p>\n\n<p>and the Char\u2010CNN algorithm in terms of classification</p>\n\n<p>accuracy and algorithm robustness.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Guangdong University of Technology", 
      "@type": "Person", 
      "name": "Zhang, Ling"
    }, 
    {
      "affiliation": "Guangdong University of Technology", 
      "@type": "Person", 
      "name": "Jiang, Wenchao"
    }, 
    {
      "affiliation": "University of Amsterdam", 
      "@id": "https://orcid.org/0000-0002-6717-9418", 
      "@type": "Person", 
      "name": "Zhao, Zhiming"
    }
  ], 
  "headline": "Short\u2010text feature expansion and classification based on nonnegative matrix factorization", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2020-09-22", 
  "url": "https://zenodo.org/record/4042991", 
  "version": "camera ready", 
  "keywords": [
    "correlation", 
    "feature extension", 
    "nonnegative matrix factorization", 
    "short text classification"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.1002/int.22290", 
  "@id": "https://doi.org/10.1002/int.22290", 
  "@type": "ScholarlyArticle", 
  "name": "Short\u2010text feature expansion and classification based on nonnegative matrix factorization"
}
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