Sentiment classification based on supervised latent n-gram analysis

  title={Sentiment classification based on supervised latent n-gram analysis},
  author={Dmitriy Bespalov and Bing Bai and Yanjun Qi and Ali Shokoufandeh},
In this paper, we propose an efficient embedding for modeling higher-order (n-gram) phrases that projects the n-grams to low-dimensional latent semantic space, where a classification function can be defined. We utilize a deep neural network to build a unified discriminative framework that allows for estimating the parameters of the latent space as well as the classification function with a bias for the target classification task at hand. We apply the framework to large-scale sentimental… CONTINUE READING
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