Sentiment Analysis and Deep Learning

This book PDF is perfect for those who love Technology & Engineering genre, written by Subarna Shakya and published by Springer Nature which was released on 01 January 2023 with total hardcover pages 987. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Sentiment Analysis and Deep Learning books below.

Sentiment Analysis and Deep Learning
Sentiment Analysis and Deep Learning
Author : Subarna Shakya
File Size : 54,6 Mb
Publisher : Springer Nature
Language : English
Release Date : 01 January 2023
ISBN : 9789811954436
Pages : 987 pages
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Sentiment Analysis and Deep Learning by Subarna Shakya Book PDF Summary

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.

Sentiment Analysis and Deep Learning

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

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.

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Deep Learning Based Approaches for Sentiment Analysis

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

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.

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Visual and Text Sentiment Analysis Through Hierarchical Deep Learning Networks

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

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

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Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks

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

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

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New Opportunities for Sentiment Analysis and Information Processing

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

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

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Examining the Impact of Deep Learning and IoT on Multi Industry Applications

Examining the Impact of Deep Learning and IoT on Multi Industry Applications by Raut, Roshani,Mihovska, Albena Dimitrova

Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms

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Supervised Machine Learning for Text Analysis in R

Supervised Machine Learning for Text Analysis in R by Emil Hvitfeldt,Julia Silge

Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance

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Sentimental Analysis and Deep Learning

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

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

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