Vassilev, A.
and Hasan, M.
(2020),
Can you tell? SSNet - a Sagittal Stratum-inspired Neural Network Framework for Sentiment Analysis, arXiv, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=931152, https://arxiv.org/abs/2006.12958
(Accessed November 23, 2024)
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Can you tell? SSNet - a Sagittal Stratum-inspired Neural Network Framework for Sentiment Analysis
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Abstract
When people try to understand nuanced language they typically process multiple input sensor modalities to complete this cognitive task. It turns out the human brain has even a specialized neuron formation, called sagittal stratum, to help us understand sarcasm. We use this biological formation as the inspiration for designing a neural network architecture that combines predictions of different models on the same text to construct a robust, accurate and computationally efficient classifier for sentiment analysis. Experimental results on representative benchmark datasets and comparisons to other methods show the advantages of the new network architecture. [This is an updated version to the paper published in June 2020].Citation
arXiv
Volume
2006
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Keywords
natural language processing, machine learning, deep learning, artificial intelligence
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Created September 23, 2020, Updated December 2, 2020