Visual And Text Sentiment Analysis Through Hierarchical Deep Learning Networks PDF Download

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Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks

Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks
Author: Arindam Chaudhuri
Publisher: Springer
Total Pages: 98
Release: 2019-04-06
Genre: Computers
ISBN: 9811374740

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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

Emerging Technologies in Data Mining and Information Security
Author: Aboul Ella Hassanien
Publisher: Springer Nature
Total Pages: 922
Release: 2021-05-04
Genre: Technology & Engineering
ISBN: 9813343672

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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.


Multi-Modal Sentiment Analysis

Multi-Modal Sentiment Analysis
Author: Hua Xu
Publisher: Springer Nature
Total Pages: 278
Release: 2023-11-26
Genre: Technology & Engineering
ISBN: 9819957761

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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.


Deep Learning-Based Approaches for Sentiment Analysis

Deep Learning-Based Approaches for Sentiment Analysis
Author: Basant Agarwal
Publisher: Springer Nature
Total Pages: 326
Release: 2020-01-24
Genre: Technology & Engineering
ISBN: 9811512167

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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.


Deep Learning and Reinforcement Learning

Deep Learning and Reinforcement Learning
Author:
Publisher: BoD – Books on Demand
Total Pages: 132
Release: 2023-11-15
Genre: Computers
ISBN: 1803569506

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Deep learning and reinforcement learning are some of the most important and exciting research fields today. With the emergence of new network structures and algorithms such as convolutional neural networks, recurrent neural networks, and self-attention models, these technologies have gained widespread attention and applications in fields such as natural language processing, medical image analysis, and Internet of Things (IoT) device recognition. This book, Deep Learning and Reinforcement Learning examines the latest research achievements of these technologies and provides a reference for researchers, engineers, students, and other interested readers. It helps readers understand the opportunities and challenges faced by deep learning and reinforcement learning and how to address them, thus improving the research and application capabilities of these technologies in related fields.


Images as Data for Social Science Research

Images as Data for Social Science Research
Author: Nora Webb Williams
Publisher: Cambridge University Press
Total Pages: 104
Release: 2020-08-13
Genre: Political Science
ISBN: 1108852181

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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.


Multimodal Sentiment Analysis

Multimodal Sentiment Analysis
Author: Soujanya Poria
Publisher: Springer
Total Pages: 214
Release: 2018-10-24
Genre: Medical
ISBN: 3319950207

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This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches. Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.


Recent Developments in Machine and Human Intelligence

Recent Developments in Machine and Human Intelligence
Author: Rajest, S. Suman
Publisher: IGI Global
Total Pages: 383
Release: 2023-09-11
Genre: Computers
ISBN: 1668491915

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Establishing the means to improve performance in healthy, clinical, and military populations has long been a focus of study in the psychological and brain sciences. However, a major obstacle to this goal is generating individualized performance phenotypes that allow for the design of interventions that are tailored to the specific needs of the individual. Recent developments in artificial intelligence (AI) have qualified for the development of precision approaches that consider individual differences, allowing, for example, the establishment of individualized training, preparation, and recuperation programs optimal for an individual’s cognitive and biological phenotype. Corollary developments in AI have proven that combining domain expertise and stakeholder insights can considerably improve AI’s quality, performance, and dependability in the psychology and brain sciences. Recent Developments in Machine and Human Intelligence studies original empirical work, literature reviews, and methodological papers that establish and validate precision AI methods for human performance optimization with a focus on modeling individual differences via state-of-the-art computational methods and investigating how domain expertise and human judgment can improve the performance of AI methods. The topics are crafted in such a way as to cover all the areas of artificial and human intelligence that require AI for further development. This book contains algorithms and techniques that are explained with the help of developed source code and encompasses the readiness and needs for advancements in managing yet another pandemic in the future. It is designed for academicians, scientists, research scholars, professors, graduates, undergraduates, and students.


Artificial Intelligence and Mobile Services – AIMS 2021

Artificial Intelligence and Mobile Services – AIMS 2021
Author: Yi Pan
Publisher: Springer Nature
Total Pages: 123
Release: 2022-02-13
Genre: Computers
ISBN: 3030960331

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This book constitutes the proceedings of the 10th International Conference on Artificial Intelligence and Mobile Services, AIMS 2021, held as a virtual conference as part of SCF 2021, during December 10-14, 2021. The 9 full presented were carefully reviewed and selected from 20 submissions. They cover topics in AI Modeling, AI Analysis, AI and Mobile Applications, AI Architecture, AI Management, AI Engineering, mobile backend as a service (MBaaS), user experience of AI and mobile services.