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Sentiment Analysis and Deep Learning de Subarna Shakya

Sentiment Analysis and Deep Learning: Advances in Intelligent Systems and Computing

Editat de Subarna Shakya, Ke-Lin Du, Klimis Ntalianis
en Limba Engleză Paperback – 2 ian 2023

ABORDAREA PRACTICĂ a acestui volum este definită de tranziția directă de la modelele teoretice de inteligență artificială la implementări software riguroase. Suntem de părere că valoarea principală a lucrării rezidă în capacitatea sa de a prezenta nu doar algoritmi, ci și modul în care aceștia interacționează cu datele reale, nestructurate, pentru a extrage semantică și percepții umane. Pe linia practică a volumului Sentiment Analysis Unveiled, dar cu focus pe arhitecturi complexe de învățare profundă, această colecție de lucrări de la conferința ICSADL 2022 oferă o perspectivă tehnică asupra automatizării proceselor de business prin analiza emoțiilor în timp real.

Apreciem structura progresivă a cărții, care ghidează cititorul prin studii de caz specifice: de la clasificarea imaginilor hiperspectrale la utilizarea tehnicilor Naive Bayes pentru analiza fluxurilor Twitter și implementarea modelelor BERT personalizate. Organizarea materialului reflectă o viziune holistică asupra domeniului, integrând analiza sentimentelor cu tehnologii complementare precum IoT și securitatea plăților mobile. În contextul operei editorului Subarna Shakya, acest volum completează cercetările sale anterioare, precum Mobile Computing and Sustainable Informatics sau Proceedings of Third International Conference on Sustainable Expert Systems, mutând centrul de greutate de la infrastructură spre interpretarea inteligentă a conținutului generat de utilizatori. Textul este dens în detalii tehnice, oferind specificații clare pentru modelele Long Short-Term Memory (LSTM) și rețelele neuronale recurente, fiind un instrument de lucru esențial pentru cercetătorii care urmăresc performanța în procesarea limbajului natural.

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Specificații

ISBN-13: 9789811954429
ISBN-10: 9811954429
Pagini: 1052
Ilustrații: XVIII, 1014 p. 481 illus., 402 illus. in color. In 2 volumes, not available separately.
Dimensiuni: 155 x 235 x 53 mm
Greutate: 1.77 kg
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Seria Advances in Intelligent Systems and Computing

Locul publicării:Singapore, Singapore

De ce să citești această carte

Recomandăm această carte inginerilor de date și cercetătorilor în AI care doresc să implementeze soluții de analiză a sentimentelor dincolo de nivelul de bază. Cititorul câștigă acces la metodologii testate pentru procesarea datelor volumetrice, beneficiind de exemple concrete ce utilizează BERT, RNN și LSTM. Este o resursă tehnică solidă pentru oricine dorește să transforme datele nestructurate în informații de business acționabile.

Despre autor

Editorul principal, Subarna Shakya, este un profesor și cercetător recunoscut în cadrul Universității Tribhuvan din Nepal, specializat în ingineria sistemelor și informatică. Cu o activitate editorială prolifică în cadrul Springer Nature, Shakya a coordonat numeroase conferințe internaționale axate pe sustenabilitate digitală, sisteme expert și tehnologii mobile. Expertiza sa în integrarea tehnologiilor inteligente în ecosisteme reziliente este reflectată în acest volum prin selecția riguroasă a lucrărilor care îmbină rigoarea academică cu aplicabilitatea industrială imediată în domeniul analizei sentimentelor.

Descriere scurtă

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. 

Cuprins

Ranking roughly tourist destinations using BERT based semantic search.- Discerning the Application of Virtual Laboratory in Curriculum Transaction of Software Engineering Lab Course from the Lens of Critical Pedagogy.- Drought Prediction using Recurrent Neural Networks and Long Short-Term Memory model.- A Deep Learning Framework for Classification of Hyperspectral Images.- Improved Security on Mobile Payments Using IMEI Verification.- Analytics and Data Computing for the Development of the Concept Digitalization in Business and Economic Structures.- Smart Door Locking System using IoT -A Security for Railway Engine Pilots.- Designing and Implementing a Distributed Database for Microservices Cloud-Based Online Travel Portal.- A comparative study of a new customized bert for sentiment analysis.- Twitter Sentiment Analysis Using Naive Bayes Based Machine Learning Technique.- Rainfall Forecasting System Using Machine Learning Technique and IoT Technology for a Localized Region.- Infrastructure as Code (IaC): Insights on Various Platforms.- Breast Cancer Prediction using different Machine Learning Algorithm.- A Proposed System for Understanding the Consumer Opinion of a Product Using Sentiment Analysis.- Comparative study of Machine Learning and Deep learning for Fungi classification.- Personality as a predictor of Computer Science Students' Learning Motivation.- Prediction and analysis of liver disease using extreme learning machine.- Deep-learning based quality assurance of silicon detectors in Compact Muon Solenoid experiment.- An Effectual Analytics and Approach for Avoidance of Malware in Android using Deep Neural Networks.- A One-Stop Service Provider for Farmers Using Machine Learning.- Fuzzy Logic Based Control of SEPIC Converter for Vehicle to Grid Application.- Social media mining to detect mental health disorders using Machine learning.- Using Deep Learning Models for Crop and Weed Classification at Early Stage.- FaceMask detection and social distancing usingMachine Learning with Haarcascade algorithm.

Notă biografică

Dr. Prof. Subarna Shakya is currently a 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 MSc and PhD degrees in Computer Engineering from the Lviv Polytechnic National University, Ukraine, 1996 and 2000 respectively. His research area includes E-Government system, Computer Systems and Simulation, Distributed and Cloud Computing, Software Engineering and Information System, Computer Architecture, Information Security for E-Government, and Multimedia system. 
Dr. Ke-Lin Du has been a research scientist at Center for Signal Processing and Communications, Department of Electrical and Computer Engineering, Concordia University since 2001, where he became an Affiliate Associate Professor in 2011. He received a PhD degree in electrical engineering from Huazhong University of Science and Technology in 1998. He has published 5 textbooks, 50 papers, and holds 6 granted U.S. Patents. Presently, he is on the editorial boards of IEEE Spectrum Chinese Edition, IET Signal Processing, Circuits Systems & Signal Processing, Mathematics, and AI. He served as program chair of dozens of conferences. His research area includes wireless communications, signal processing, and machine learning. He has been a Senior Member of the IEEE since 2009.
Dr. Klimis Ntalianis is a full professor at the University of West Attica, Athens, GREECE. He has worked as Senior Researcher in multi-million research and development projects, funded by the General Secretariat of Research and Technology of Greece (GSRT), the Research Promotion Foundation of Cyprus (RPF), the Information Society S.A. of Greece and the European Union. He is also serving as a Senior Project Proposal Evaluator for GSRT, RPF, the European Union, the Natural Sciences and Engineering Research Council of Canada and the National Science Center of Poland. In parallel he is a member of several master theses and Phd evaluation committees in Greece, Cyprus, Germany and India. He is also serving as promotion evaluator for Saudi Arabia and academic staff. He has served as general chair in several conferences (IEEE etc.). Dr. Ntalianis has published more than 160 scientific papers in international journals, books and conferences. His main research interests include social computing, multimedia analysis and information security. 

Caracteristici

Presents research works in the field of sentiment analysis and deep learning Provides original works presented at ICSADL 2022 held in Songkhla, Thailand Serves as a reference for researchers and practitioners in academia and industry