Advances in Data Science and Management : Proceedings of ICDSM 2021

• Record Nr.: UNINA9910743219203321
• Autore: Borah Samarjeet
• Pubbl/distr/stampa: Singapore : , : Springer Singapore Pte. Limited, , 2022; ©2022
• ISBN: 9789811656859; 9811656851; 9789811656842; 9811656843
• Descrizione fisica: 1 online resource (620 pages)
• Collana: Lecture Notes on Data Engineering and Communications Technologies ; ; v.86
• Altri autori (Persone): MishraSambit Kumar; MishraBrojo Kishore; BalasValentina Emilia; PolkowskiZdzislaw
• Disciplina: 658.4030285
• Soggetti: Machine learning; Big data
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Preface -- Contents -- Editors and Contributors -- Machine Learning Applications for Data Science -- Linguistic Information for Decision-Making Using SVM -- 1 Introduction -- 2 Problem Formulation -- 3 Result Analysis -- 4 Conclusion -- References -- Generalization of Blocks Linked with Query Response Using Meta-heuristic Approach -- 1 Introduction -- 2 Review of Literature -- 3 Application of Particle Swarm Optimization Towards Query Response as Well as Streaming the Blocks -- 4 Experimental Analysis -- 5 Discussion and Future Direction -- 6 Conclusion -- References -- Use of Big Data Analysis in Data Management Aspects -- 1 Introduction -- 2 Characteristics of Big Data -- 3 Big Data Storage and Management -- 4 Supply Chain and Performance Management -- 5 Quality Management and Improvement -- 6 Risk Management and Fraud Detection in Big Data -- 7 Experimental Analysis -- 7.1 Proposed ; Algorithm -- 7.2 Comparison Analysis -- 8 Conclusion -- References
• Sommario/riassunto: This book, 'Advances in Data Science and Management,' presents a collection of research and analysis from the second International Conference on Data Science and Management (ICDSM 2021). Edited by Samarjeet Borah, Sambit Kumar Mishra, Brojo Kishore Mishra, Valentina Emilia Balas, and Zdzislaw Polkowski, it is part of a series focused on cutting-edge engineering approaches to data technologies. The volume is divided into four parts, addressing topics such as machine learning applications, data analysis in biomedical and biological fields, computer security, and the use of big data in various sectors. The book serves as a resource for researchers and professionals interested in the latest developments in data science, offering insights into practical applications and theoretical advancements.