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文章基本信息

  • 标题:Probabilistic Neural Network and Word Embedding for Sentiment Analysis
  • 作者:Saqib Alam ; Nianmin Yao
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2018
  • 卷号:9
  • 期号:7
  • DOI:10.14569/IJACSA.2018.090708
  • 出版社:Science and Information Society (SAI)
  • 摘要:In the present days, Artificial Intelligence (AI) is an attractive area of research along with numerous practicable purposes and vigorous subject matters and tasks, such as, understand speech, natural language, diagnose medicine and support basic research. In this study deep learning (DL) techniques, i.e. Probabilistic Neural Network (PNN) and Word Embedding (WE) will be used for sentiment analysis. The entire proposed framework will be divided into three phases: (a) normalization, (b) word vectorization, and (c) execution of proposed model.
  • 关键词:Deep learning; probabilistic neural network; word embedding; sentiment analysis
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