Sentiment Analysis And Deep Learning
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Deep Learning Based Approaches For Sentiment Analysis
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Author : Basant Agarwal
language : en
Publisher: Springer Nature
Release Date : 2020-01-24
Deep Learning Based Approaches For Sentiment Analysis written by Basant Agarwal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-24 with Technology & Engineering categories.
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.
Learning Tensorflow
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Author : Tom Hope
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-08-09
Learning Tensorflow written by Tom Hope and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-09 with Computers categories.
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
Sentiment Analysis For Social Media
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Author : Carlos A. Iglesias
language : en
Publisher: MDPI
Release Date : 2020-04-02
Sentiment Analysis For Social Media written by Carlos A. Iglesias and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Technology & Engineering categories.
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.
Sentiment Analysis And Deep Learning
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Author : Subarna Shakya
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Sentiment Analysis And Deep Learning written by Subarna Shakya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Technology & Engineering categories.
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.
Visual And Text Sentiment Analysis Through Hierarchical Deep Learning Networks
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Author : Arindam Chaudhuri
language : en
Publisher: Springer
Release Date : 2019-04-06
Visual And Text Sentiment Analysis Through Hierarchical Deep Learning Networks written by Arindam Chaudhuri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-06 with Computers categories.
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.
Opinions Sentiment And Emotion In Text
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Author : Bing Liu
language : en
Publisher: Cambridge University Press
Release Date : 2015-06-04
Opinions Sentiment And Emotion In Text written by Bing Liu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-04 with Computers categories.
This book gives a comprehensive introduction to all the core areas and many emerging themes of sentiment analysis.
Sentimental Analysis And Deep Learning
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Author : Subarna Shakya
language : en
Publisher: Springer Nature
Release Date : 2021-10-25
Sentimental Analysis And Deep Learning written by Subarna Shakya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-25 with Technology & Engineering categories.
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.
Natural Language Processing For Global And Local Business
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Author : Fatih Pinarbasi
language : en
Publisher:
Release Date : 2020
Natural Language Processing For Global And Local Business written by Fatih Pinarbasi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computational linguistics categories.
"This book explores the theoretical and practical phenomenon of natural language processing through different languages and platforms in terms of today's conditions"--
Sentiment Analysis In Social Networks
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Author : Federico Alberto Pozzi
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-10-06
Sentiment Analysis In Social Networks written by Federico Alberto Pozzi and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-06 with Computers categories.
The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network analysis - Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network mining - Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics