Sentiment analysis with tree-structured gated recurrent units

7Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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.

Cite

CITATION STYLE

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free