Sentimental Analysis And Deep Learning

Author : Arindam Chaudhuri
Publisher : Springer
Page : 98 pages
File Size : 50,9 Mb
Release : 2019-04-06
Category : Computers
ISBN : 9789811374746

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Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks by Arindam Chaudhuri Pdf

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.

Author : Basant Agarwal,Richi Nayak,Namita Mittal,Srikanta Patnaik
Publisher : Springer Nature
Page : 326 pages
File Size : 54,9 Mb
Release : 2020-01-24
Category : Technology & Engineering
ISBN : 9789811512162

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Deep Learning-Based Approaches for Sentiment Analysis by Basant Agarwal,Richi Nayak,Namita Mittal,Srikanta Patnaik Pdf

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.

Author : Subarna Shakya,Ke-Lin Du,Klimis Ntalianis
Publisher : Springer Nature
Page : 987 pages
File Size : 52,5 Mb
Release : 2023-01-01
Category : Technology & Engineering
ISBN : 9789811954436

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Sentiment Analysis and Deep Learning by Subarna Shakya,Ke-Lin Du,Klimis Ntalianis Pdf

This book gathers selected papers presented at International Conference on Sentimental Analysis and Deep Learning (ICSADL 2022), jointly organized by Tribhuvan University, Nepal and Prince of Songkla University, Thailand during 16 – 17 June, 2022. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes.

Author : Subarna Shakya,Valentina Emilia Balas,Sinchai Kamolphiwong,Ke-Lin Du
Publisher : Springer Nature
Page : 1023 pages
File Size : 44,9 Mb
Release : 2021-10-25
Category : Technology & Engineering
ISBN : 9789811651571

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Sentimental Analysis and Deep Learning by Subarna Shakya,Valentina Emilia Balas,Sinchai Kamolphiwong,Ke-Lin Du Pdf

This book gathers selected papers presented at the International Conference on Sentimental Analysis and Deep Learning (ICSADL 2021), jointly organized by Tribhuvan University, Nepal; Prince of Songkla University, Thailand; and Ejesra during June, 18–19, 2021. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes. Meanwhile, deep learning emerges as the revolutionary paradigm with its extensive data-driven representation learning architectures. This book discusses all theoretical aspects of sentimental analysis, deep learning and related topics.

Author : Sharaff, Aakanksha,Sinha, G. R.,Bhatia, Surbhi
Publisher : IGI Global
Page : 311 pages
File Size : 49,9 Mb
Release : 2021-06-25
Category : Computers
ISBN : 9781799880639

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New Opportunities for Sentiment Analysis and Information Processing by Sharaff, Aakanksha,Sinha, G. R.,Bhatia, Surbhi Pdf

Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts. New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students.

Author : Mundada, Monica R.,Seema, S.,K.G., Srinivasa,Shilpa, M.
Publisher : IGI Global
Page : 293 pages
File Size : 43,9 Mb
Release : 2021-12-17
Category : Computers
ISBN : 9781799881636

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Deep Learning Applications for Cyber-Physical Systems by Mundada, Monica R.,Seema, S.,K.G., Srinivasa,Shilpa, M. Pdf

Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.

Author : Anonim
Publisher : Unknown
Page : 326 pages
File Size : 46,9 Mb
Release : 2020
Category : Data mining
ISBN : 9811512175

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Deep Learning-based Approaches for Sentiment Analysis by Anonim Pdf

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.

Author : Fatih Pinarbași,Nurdan Öncel Taşkıran
Publisher : Unknown
Page : 128 pages
File Size : 48,7 Mb
Release : 2020
Category : Computational linguistics
ISBN : 1799842401

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Natural Language Processing for Global and Local Business by Fatih Pinarbași,Nurdan Öncel Taşkıran Pdf

"This book explores the theoretical and practical phenomenon of natural language processing through different languages and platforms in terms of today's conditions"--

Author : Mayukh Sharma, Ilanthenral Kandasamy,W.B. Vasantha
Publisher : Infinite Study
Page : 14 pages
File Size : 42,7 Mb
Release : 2024-06-15
Category : Mathematics
ISBN : 8210379456XXX

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Comparison of neutrosophic approach to various deep learning models for sentiment analysis by Mayukh Sharma, Ilanthenral Kandasamy,W.B. Vasantha Pdf

Deep learning has been widely used in numerous real-world engineering applications and for classification problems. Real-world data is present with neutrality and indeterminacy, which neutrosophic theory captures clearly. Though both are currently developing research areas, there has been little study on their interlinking. We have proposed a novel framework to implement neutrosophy in deep learning models. Instead of just predicting a single class as output, we have quantified the sentiments using three membership functions to understand them better. Our proposed model consists of two blocks, feature extraction, and feature classification.

Author : Tom Hope,Yehezkel S. Resheff,Itay Lieder
Publisher : "O'Reilly Media, Inc."
Page : 242 pages
File Size : 40,9 Mb
Release : 2017-08-09
Category : Computers
ISBN : 9781491978481

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Learning TensorFlow by Tom Hope,Yehezkel S. Resheff,Itay Lieder Pdf

Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. You’ll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you’ll know how to build and deploy production-ready deep learning systems in TensorFlow. Get up and running with TensorFlow, rapidly and painlessly Learn how to use TensorFlow to build deep learning models from the ground up Train popular deep learning models for computer vision and NLP Use extensive abstraction libraries to make development easier and faster Learn how to scale TensorFlow, and use clusters to distribute model training Deploy TensorFlow in a production setting

Author : Soni Sweta
Publisher : Springer Nature
Page : 116 pages
File Size : 49,6 Mb
Release : 2024-06-15
Category : Electronic
ISBN : 9789819724741

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Sentiment Analysis and its Application in Educational Data Mining by Soni Sweta Pdf

Author : Bing Liu
Publisher : Cambridge University Press
Page : 451 pages
File Size : 42,9 Mb
Release : 2020-10-15
Category : Business & Economics
ISBN : 9781108486378

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Sentiment Analysis by Bing Liu Pdf

A comprehensive introduction to computational analysis of sentiments, opinions, emotions, and moods. Now including deep learning methods.

Author : Carlos A. Iglesias,Antonio Moreno
Publisher : MDPI
Page : 152 pages
File Size : 48,8 Mb
Release : 2020-04-02
Category : Technology & Engineering
ISBN : 9783039285723

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Sentiment Analysis for Social Media by Carlos A. Iglesias,Antonio Moreno Pdf

Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection.

Author : Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
Publisher : IGI Global
Page : 674 pages
File Size : 40,7 Mb
Release : 2019-12-13
Category : Computers
ISBN : 9781522596455

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Handbook of Research on Emerging Trends and Applications of Machine Learning by Solanki, Arun,Kumar, Sandeep,Nayyar, Anand Pdf

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

Author : Ahmed Menshawy
Publisher : Packt Publishing Ltd
Page : 442 pages
File Size : 42,9 Mb
Release : 2018-02-28
Category : Computers
ISBN : 9781788395762

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Deep Learning By Example by Ahmed Menshawy Pdf

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner Key Features Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Book Description Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. What you will learn Understand the fundamentals of deep learning and how it is different from machine learning Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning Increase the predictive power of your model using feature engineering Understand the basics of deep learning by solving a digit classification problem of MNIST Demonstrate face generation based on the CelebA database, a promising application of generative models Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation Who this book is for This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial.