Advances in neural network models and deep learning mark great impact on sentiment analysis, where models based on recursive or convolutional neural networks show state-of-the-art results leaving behind non-neural models like SVM or traditional lexicon-based approaches. We present Tree-Structured Gated Recurrent Unit network, which exhibits greater simplicity in comparison to the current state of the art in sentiment analysis, Tree-Structured LSTM model.
CITATION STYLE
Kuta, M., Morawiec, M., & Kitowski, J. (2017). Sentiment analysis with tree-structured gated recurrent units. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10415 LNAI, pp. 74–82). Springer Verlag. https://doi.org/10.1007/978-3-319-64206-2_9
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