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Sentimental Analysis and Deep Learning

Proceedings of ICSADL 2021

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Subarna Shakya

    1. Institute of Engineering, Tribhuvan University, Pulchowk Campus, Lalitpur, Nepal

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  2. Valentina Emilia Balas

    1. Intelligent Systems Research Centre, Aurel Vlaicu University of Arad, Arad, Romania

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  3. Sinchai Kamolphiwong

    1. Songkla University, Songkhla, Thailand

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  4. Ke-Lin Du

    1. Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada

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  • Presents research works in the field of sentimental analysis and deep learning
  • Provides original works presented at ICSADL 2021 held in Songkhla, Thailand
  • Serves as a reference for researchers and practitioners in academia and industry

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 1408)

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Table of contents (77 papers)

  1. Front Matter

    Pages i-xxxiii
    Download chapter PDF

  2. Analysis of Healthcare Industry Using Machine Learning Approach: A Case Study in Bengaluru Region

    • Poornima Taranath, Sweta Das, S. Gowrishankar
    Pages 1-13

  3. Dynamic Document Localization for Efficient Mining

    • P. Sijin, H. N. Champa
    Pages 15-29

  4. SentiSeries: A Trilogy of Customer Reviews, Sentiment Analysis and Time Series

    • Aishwarya Asesh
    Pages 31-45

  5. Video Summarization Using Fully Convolutional Residual Dense Network

    • Anil Singh Parihar, Ritvik Mittal, Himanshu, Prashuk Jain
    Pages 47-58

  6. An Efficient Deep Learning Approach for Detecting Pneumonia Using the Convolutional Neural Network

    • Anik Kumar Saha, Md. Muhaimenur Rahman
    Pages 59-68

  7. QMCDS: Quantum Memory for Cloud Data Storage

    • Ankit Sharma, Indra Kumar Sahu, Manisha J. Nene
    Pages 69-78

  8. A Study Towards Bangla Fake News Detection Using Machine Learning and Deep Learning

    • Elias Hossain, Md. Nadim Kaysar, Abu Zahid Md. Jalal Uddin Joy, Md. Mizanur Rahman, Wahidur Rahman
    Pages 79-95

  9. A Deep Learning Approach to Analyze the Propagation of Pandemic in America

    • Paola G. Vinueza-Naranjo, Angel F. Vinueza-Naranjo, Hieda A. Nascimento-Silva
    Pages 97-111

  10. Graph Convolution-Based Joint Learning of Rumor with Content, User Credibility, Propagation Context, and Cognitive as Well as Emotion Signals

    • Prajna Nagaraj, Bhaskarjyoti Das
    Pages 113-128

  11. Deep Learning-Based Real-Time Object Classification and Recognition Using Supervised Learning Approach

    • J. Harikrishna, Ch. Rupa, R. Gireesh
    Pages 129-139

  12. Single-Channel Speech Enhancement in Modulation Domain Using Particle Swarm Optimization

    • Kalpana Ghorpade, Arti Khaparde
    Pages 141-153

  13. Pneumonia and Diabetic Retinopathy Detection Using Deep Learning Algorithm

    • Meera Ghaskadvi, Sakshi Khochare, Rozebud Gonsalves, Prajakta Dhamanskar
    Pages 155-175

  14. Design of IoT-Based Improved Multimodal Ant Colony Optimızation (MM-ACO) Algorithm for Real-Time Applications

    • Mohammed Khalid Kaleem, Kassahun Azezew, Smegnew Asemie
    Pages 177-184

  15. An Interview Transcriber Using Natural Language Processing

    • G. R. Deeba Lakshmi, Jayavrinda Vrindavanam, Anshika Shukla, Rahul
    Pages 185-197

  16. Plagiarism Detection for Source Codes and Texts

    • Syed Yasmeen, Munjuluri Prathyusha, Malisetty Rajeswari, Padmanabhuni Srujana, K. Ashesh
    Pages 199-208

  17. Investigation of Kinetic Energy Harvesting from Human Body Motion Activities Using Free/Impact Electromagnetic Generator

    • Athern Aloysius, M. K. A. Ahamed Khan, Wei Hong Lim, Manicam Ramaswamy, Sridevi, Deisy et al.
    Pages 209-221

  18. Automated Determination of Critical Temperature

    • Abhishek Deshpande, Jatin Pardhi, Gokul Bisen
    Pages 223-236

  19. ANN-based Hybridization Approach for Detection of Cardiac Disease

    • N. Shwetha, N. Gangadhar, Mahesh B. Neelagar, K. C. Shilpa
    Pages 237-253

  20. The Implementation of Enhanced K-Strange Points Clustering Method in Classifying Undergraduate Thesis Titles

    • Malcolm Andrew Madeira, Teslin Jacob
    Pages 255-274
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Keywords

About this book

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.

Editors and Affiliations

  • Institute of Engineering, Tribhuvan University, Pulchowk Campus, Lalitpur, Nepal

    Subarna Shakya

  • Intelligent Systems Research Centre, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  • Songkla University, Songkhla, Thailand

    Sinchai Kamolphiwong

  • Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada

    Ke-Lin Du

About the editors

Dr. Prof. Subarna Shakya is currently Professor of Computer Engineering, Department of Electronics and Computer Engineering, Central Campus, Institute of Engineering, Pulchowk, Tribhuvan University, Coordinator (IOE), LEADER Project (Links in Europe and Asia for engineering, eDucation, Enterprise and Research exchanges), ERASMUS MUNDUS. He received M.Sc. and Ph.D. degrees in Computer Engineering from the Lviv Polytechnic National University, Ukraine, 1996 and 2000, respectively. His research area includes e-government systems, computer systems and simulation, distributed  and cloud computing,  software engineering and information systems, computer architecture, information security for e-government, multimedia systems.



Dr. Valentina E. Balas is currently Full Professor at “Aurel Vlaicu” University of Arad, Romania. She is Author of more than 300 research papers. Her research interests are in intelligent systems, fuzzy control, soft computing. She is Editor-in Chief to International Journal of Advanced Intelligence Paradigms (IJAIP) and to IJCSE. He is Member of EUSFLAT, ACM and a SM IEEE, Member in TC–EC and TC-FS (IEEE CIS), TC–SC (IEEE SMCS), Joint Secretary FIM. 
Dr. Sinchai Kamolphiwong is Director of CNR (Centre for Network Research), Prince of Songkla University, Department of Computer Engineering, Songkhla, Thailand. He had completed his Ph.D. in the University of New South Wales, Australia. He has secured awards and research grants in reputed organization. His research interest includes computer networks, tele-medicine and real-time communications.
 
Dr. Ke-Lin Du is Research scientist at Center for Signal Processing and Communications, Department of Electrical and Computer Engineering, Concordia University, since 2001, where he became Affiliate Associate Professor in 2011. His research area includes signal processing, wireless communications and soft computing.

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