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Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks

2019-04-06 Computers
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Release : 2019-04-06
Genre : Computers
Kind : eBook
Book Rating : 740/5 ( reviews)

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Book Synopsis Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks by : Arindam Chaudhuri

Download or read book Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks written by Arindam Chaudhuri. This book was released on 2019-04-06. Available in PDF, EPUB and Kindle. Book excerpt: 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 assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.

Emerging Technologies in Data Mining and Information Security

2021-05-04 Technology & Engineering
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Release : 2021-05-04
Genre : Technology & Engineering
Kind : eBook
Book Rating : 672/5 ( reviews)

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Book Synopsis Emerging Technologies in Data Mining and Information Security by : Aboul Ella Hassanien

Download or read book Emerging Technologies in Data Mining and Information Security written by Aboul Ella Hassanien. This book was released on 2021-05-04. Available in PDF, EPUB and Kindle. Book excerpt: This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers and case studies related to all the areas of data mining, machine learning, Internet of things (IoT) and information security.

Deep Learning-Based Approaches for Sentiment Analysis

2020-01-24 Technology & Engineering
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Release : 2020-01-24
Genre : Technology & Engineering
Kind : eBook
Book Rating : 167/5 ( reviews)

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Book Synopsis Deep Learning-Based Approaches for Sentiment Analysis by : Basant Agarwal

Download or read book Deep Learning-Based Approaches for Sentiment Analysis written by Basant Agarwal. This book was released on 2020-01-24. Available in PDF, EPUB and Kindle. Book excerpt: This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field.

Images as Data for Social Science Research

2020-08-13 Political Science
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Release : 2020-08-13
Genre : Political Science
Kind : eBook
Book Rating : 181/5 ( reviews)

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Book Synopsis Images as Data for Social Science Research by : Nora Webb Williams

Download or read book Images as Data for Social Science Research written by Nora Webb Williams. This book was released on 2020-08-13. Available in PDF, EPUB and Kindle. Book excerpt: Images play a crucial role in shaping and reflecting political life. Digitization has vastly increased the presence of such images in daily life, creating valuable new research opportunities for social scientists. We show how recent innovations in computer vision methods can substantially lower the costs of using images as data. We introduce readers to the deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. We then provide guidance and specific instructions for scholars interested in using these methods in their own research.

Multi-Modal Sentiment Analysis

2023-11-26 Technology & Engineering
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Release : 2023-11-26
Genre : Technology & Engineering
Kind : eBook
Book Rating : 761/5 ( reviews)

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Book Synopsis Multi-Modal Sentiment Analysis by : Hua Xu

Download or read book Multi-Modal Sentiment Analysis written by Hua Xu. This book was released on 2023-11-26. Available in PDF, EPUB and Kindle. Book excerpt: The natural interaction ability between human and machine mainly involves human-machine dialogue ability, multi-modal sentiment analysis ability, human-machine cooperation ability, and so on. To enable intelligent computers to have multi-modal sentiment analysis ability, it is necessary to equip them with a strong multi-modal sentiment analysis ability during the process of human-computer interaction. This is one of the key technologies for efficient and intelligent human-computer interaction. This book focuses on the research and practical applications of multi-modal sentiment analysis for human-computer natural interaction, particularly in the areas of multi-modal information feature representation, feature fusion, and sentiment classification. Multi-modal sentiment analysis for natural interaction is a comprehensive research field that involves the integration of natural language processing, computer vision, machine learning, pattern recognition, algorithm, robot intelligent system, human-computer interaction, etc. Currently, research on multi-modal sentiment analysis in natural interaction is developing rapidly. This book can be used as a professional textbook in the fields of natural interaction, intelligent question answering (customer service), natural language processing, human-computer interaction, etc. It can also serve as an important reference book for the development of systems and products in intelligent robots, natural language processing, human-computer interaction, and related fields.

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