속성선택방법과 워드임베딩 및 BOW (Bag-of-Words)를 결합한 오피니언 마이닝 성과에 관한 연구

' 속성선택방법과 워드임베딩 및 BOW (Bag-of-Words)를 결합한 오피니언 마이닝 성과에 관한 연구' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Feature selection
  • Machine learning
  • Opinion mining
  • Sentiment analysis
  • word embedding
  • 감성분석
  • 머신 러닝
  • 속성 선택
  • 오피니언마이닝
  • 워드 임베딩
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
2,464 0

0.0%

' 속성선택방법과 워드임베딩 및 BOW (Bag-of-Words)를 결합한 오피니언 마이닝 성과에 관한 연구' 의 참고문헌

  • W2vlda : almost unsupervised system for aspect based sentiment analysis
  • Using Twitter trust network for stock market analysis
    Y. Ruan [2018]
  • Twitter brand sentiment analysis : A hybrid system using n-gram analysis and dynamic artificial neural network
    M. Ghiassi [2013]
  • Tweet sentiment analysis with classifier ensembles
  • The Random Subspace Method for Constructing Decision Forests
    T. K. Ho [1998]
  • Stock trend prediction based on fractal feature selection and support vector machine
    L. P. Ni [2011]
  • Stacked Generalization
  • Social media contents based sentiment analysis and prediction system
    S. Yoo [2018]
  • Sentiment classification : The contribution of ensemble learning
    G. Wang [2014]
  • Random forests
    L. Breiman [2001]
  • Opinion mining using ensemble text hidden Markov models for text classification
    M. Kang [2018]
  • Multi-class sentiment classification : The experimental comparisons of feature selection and machine learning algorithms
    Y. Liu [2017]
  • Modeling public mood and emotion: Blog and news sentiment and socio-economic phenomena
    M. Y. Chen [2017]
  • Examining the influence of stock market variables on microblogging sentiment
  • Efficient estimation of word representations in vector space
  • Current state of text sentiment analysis from opinion to emotion mining
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    F. Corea [2016]
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    J. Blitzer [2007]
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    N. Friedman [1997]
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    S. Poria [2016]
  • Artificial neural networks, 1
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    S. Menard [2002]