Business Intelligence and Data Analytics

Proceedings of BIDA 2026, Volume 1
Erscheinungsjahr 2027
ISBN: 978-3-032-40523-4
Verlag: Springer

Buch, Englisch, 606 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Smart Innovation, Systems and Technologies

This book is a collection of the high-quality research articles presented at the International Conference on Business Intelligence and Data Analytics (BIDA 2026), organized by RV Institute of Management (RVIM), Bengaluru, India, during April 2026. This book covers state-of-the-art research articles from the researchers and practitioners working in the field of business intelligence, data analytics, decision support systems, data warehousing and data mining, big data analytics, predictive and prescriptive analytics, and machine learning for business applications and their real-world applications.

Zielgruppe

Research

Autoren/Hrsg.

Verma, Abhishek

Zhang, Justin

Pandey, Avinash Chandra

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Global Research Trends in Satellite Communication Systems and Orbits: A Scientometric Analysis.- Qiskit vs. Cirq: A Controlled, Head-to-Head Evaluation with Identical Quantum Workloads.- AneurysmNet: Multi-Frame Aneurysm Detection Using EfficientNetV2 and Modality-Aware Preprocessing.- Quantum Steganography for Secure IoT Communication: A Taxonomy of Architectures, Techniques, and Open Challenges.- A Patch-wise Feature-Based Framework for Image Anomaly Detection and Localization.- Machine Learning-Based Fingerprinting of Post-Quantum and Classical Cryptographic Algorithms Using Traffic Metadata.- PolypLiteFormer: An Efficient Transformer-Based Deep Learning Model for Polyp Segmentation in Colonoscopy Images.- An Explainable Two-Stage Machine Learning Framework for Detection and Severity Classification of Nonalcoholic Fatty Liver Disease.- 3D Reconstruction for Sparse View CT Imaging using View-Independent Gaussian Splatting.- Hybrid Gen AI and NLP Framework for Legal Risk Management: Automated Compliance Violation Detec-tion in Regulatory Monitoring.- Graph-Based Machine Learning for Artist and Content Affinity Prediction.- Optimized Deep Learning and Sentiment-Aware Decision Framework for Personalized Stock Market Investment Support.- A Hybrid GNN–Collaborative Filtering–XGBoost Model for Student Examination Performance Classification.- AI Meets Advertising: Identifying Emotional Hotspots to Refine Consumer Engagement.- Business Intelligence Insights into Influencer Authenticity and Audience Trust: Evidence from Regional Language Influencers.- Etc.

Über Autor(innen)

Dr. Abhishek Verma is an Assistant Professor in the Department of Management at BITS Pilani – Pilani Campus. Before joining BITS Pilani, he was with the Indian Institute of Management Rohtak for over four years, where he worked in the Management Information Systems area. At IIM Rohtak, he led several executive management development programmes (eMDPs) in Data Analytics and held significant administrative positions such as Area chairperson and Programme chairperson for both long- and short-duration programmes. He holds a Ph.D. from the Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur. His research focuses on data analytics, particularly analysing large-scale textual and categorical data using data mining and machine learning techniques. Dr. Verma has published extensively in reputed international journals, including Safety Science, Enterprise Information Systems, Computers & Industrial Engineering, International Journal of Injury Control and Safety Promotion, and Process Safety and Environmental Protection. He has also authored several book chapters, conference papers, and business case studies and has presented his research at leading international conferences in India and abroad. In addition, he has served as the editor for the proceedings of two international conferences. He is a reviewer for journals such as Safety Science, Computers & Industrial Engineering, Management Review Quarterly, and Enterprise Information Systems.

Dr. Justin Zhang is an Associate Professor of Management Information Systems and Business Analytics in the Department of Management at Coggin College of Business, University of North Florida (UNF). He is also the Program Director of the Master of Science in Business Analytics (MSBA) program at UNF. He received his Ph.D. in Business Administration with a concentration on Management Science and Information Systems from Pennsylvania State University, University Park. His research interests include economics of information systems, knowledge management, electronic business, business process management, information security, and social networking. He is the editor-in-chief of the Journal of Global Information Management, an ABET program evaluator, and an IEEE senior member. His areas of Expertise are Business Analytics, Economics Of Information Systems, Information Security, Knowledge Management, Social Media. He did Master in Economics from Shanghai University of Finance and Economics, Shanghai, China and Bachelor of Engineering from Tongji University, Shanghai, China. He has received award of Excellence, 14th Scholars Transforming Academic Research Symposium, April 17, 2023, UNF and listed in Top 2% Most-Cited Scientists Worldwide 2023, 2024, 2025. He is editor in chief of Journal of Global Information Management (ABDC-A, ABS-2, SSCI, 2022 IF: 4.7, JCR Q2). He is member of various academic societies like IEEE, AIS, ACM, INFORMS.

Dr. Avinash Chandra Pandey is an Associate Professor in the Department of Cyber Security and Digital Forensics at the National Forensic Sciences University, Dharwad Campus, India. He specializes in Artificial Intelligence, Machine Learning, and Data Science applications across interdisciplinary domains, with research interests in Machine Learning, Natural Language Processing, and nature-inspired computing. With over a decade of teaching and research experience at UG and PG levels, he has published 50+ papers in reputed international journals and conferences, holds 4 patents, and has completed 2 sponsored research projects. Dr. Pandey currently supervises 3 Ph.D., 1 M.Tech, and numerous B.Tech projects and has previously guided 4 M.Tech and 30 B.Tech projects to completion. He serves as a reviewer for government-funded projects and leading international journals and is a sought-after resource person, delivering invited lectures at national and international conferences, STTPs, and QIP programs.