书目名称 | Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks |
编辑 | Arindam Chaudhuri |
视频video | |
概述 | Presents the latest research on hierarchical deep learning for sentiment analysis.Displays a mathematical abstraction of the sentiment analysis model in a very lucid manner.Proposes a sentiment analys |
丛书名称 | SpringerBriefs in Computer Science |
图书封面 |  |
描述 | .This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. .The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book’s novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments; stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit; evaluation of HGFRNNs with different types of recurrent units; and adaptive assignm |
出版日期 | Book 2019 |
关键词 | Sentiment Analysis; Information Retrieval; Gated Feedback Recurrent Neural Network; Text and Visual Fea |
版次 | 1 |
doi | https://doi.org/10.1007/978-981-13-7474-6 |
isbn_softcover | 978-981-13-7473-9 |
isbn_ebook | 978-981-13-7474-6Series ISSN 2191-5768 Series E-ISSN 2191-5776 |
issn_series | 2191-5768 |
copyright | The Author(s), under exclusive to Springer Nature Singapore Pte Ltd. 2019 |