Parameterized convolutional neural networks for aspect level sentiment classification

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Abstract

We introduce a novel parameterized convolutional neural network for aspect level sentiment classification. Using parameterized filters and parameterized gates, we incorporate aspect information into convolutional neural networks (CNN). Experiments demonstrate that our parameterized filters and parameterized gates effectively capture the aspect-specific features, and our CNN-based models achieve excellent results on SemEval 2014 datasets.

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APA

Huang, B., & Carley, K. M. (2018). Parameterized convolutional neural networks for aspect level sentiment classification. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 (pp. 1091–1096). Association for Computational Linguistics. https://doi.org/10.18653/v1/d18-1136

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