Advances in Big Data Analytics: Theory, Algorithms and Practices

This book provides a comprehensive and cutting-edge study on big data analytics, covering concepts such as big data analytics, multi-criteria optimization, expert and rule-based data analysis, support vector machines, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. It also explores lessons learned in applying big data to business, engineering, and healthcare, and addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence.

Format: Paperback / softback
Length: 728 pages
Publication date: 15 January 2023
Publisher: Springer Verlag, Singapore

Big data has a profound impact on various facets of our daily lives, shaping our interactions, decision-making, and understanding of the world. In response to this growing phenomenon, this book presents a comprehensive and cutting-edge exploration of big data analytics, drawing upon extensive research findings and applications developed by the author and his esteemed colleagues in related fields. Spanning a wide range of topics, the book delves into the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. Furthermore, the book explores valuable lessons learned in applying big data to business, engineering, and healthcare domains. Additionally, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence, shedding light on the potential applications of big data in the realm of intelligent systems.

Since each of the aforementioned aspects pertains to a specific domain of application, when considered collectively, the algorithms, procedures, analysis, and empirical studies presented herein provide a comprehensive overview of the advancements in big data. Consequently, this book serves as a valuable textbook for graduates with a solid foundation in big data analytics, equipping them with the knowledge and techniques to address real-world big data challenges effectively. Moreover, it serves as a practical guide for practitioners, showcasing how to apply the proposed methodologies to tackle complex and pressing big data problems.

Weight: 1122g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811636097
Edition number: 1st ed. 2022