Abstract
In this research, a novel hierarchical GFRNN-based model for analysing sentiments on multimodal content is presented. Giving due consideration for leveraging huge volume of blog contents available towards sentiment analysis, multimodal techniques are utilized here. The learning algorithm of GFRNN is based on different timescales which work as temporal convolution, and it is basically 1D convolution which is similar to 2D spatial convolution.
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© 2019 The Author(s), under exclusive to Springer Nature Singapore Pte Ltd.
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Chaudhuri, A. (2019). Conclusion. In: Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-13-7474-6_8
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DOI: https://doi.org/10.1007/978-981-13-7474-6_8
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