Relational Calculus for Actionable Knowledge

This book discusses the challenge of turning data into actionable knowledge in the field of data science, particularly in complex and dynamic environments such as Cyber-Physical and Social Systems (CPSS). It presents advanced knowledge concepts and analytics and information fusion (AIF) processes to achieve this transformation. The book is ideal for graduate students, researchers, and industry professionals interested in decision science and knowledge engineering.

Format: Paperback / softback
Length: 340 pages
Publication date: 23 January 2023
Publisher: Springer Nature Switzerland AG

The book focuses on one of the most significant challenges in the emerging field of data science: converting data into actionable knowledge to capitalize on the growing volumes of data and address their inherent complexity. While actionable knowledge has been extensively researched in management, business, and the social sciences, its connection to data mining and its evolution, known as Knowledge Discovery and Data Mining (KDD), has only recently been established in computer science and engineering. Data mining aims to extract interesting patterns from data, but until now, the patterns discovered have not always been useful for decision-makers in Socio-Technical Organizations (STO). With the advent of the Internet and connectivity, STOs have transformed into Cyber-Physical and Social Systems (CPSS) that characterize our modern world. In such complex and dynamic environments, the conventional KDD process is insufficient, and additional processes are needed to transform complex data into actionable knowledge.

The book provides readers with advanced knowledge concepts and analytics and information fusion (AIF) processes designed to deliver actionable knowledge. The authors delve into the concept of relations and their exploitation, relational calculus, and the formalization of specific dimensions of knowledge that undergo semantic growth along the AIF processes. This book serves as a valuable technical presentation of relational calculus and its application to processing chains for generating actionable knowledge. It is particularly suited for graduate students, researchers, and industry professionals interested in decision science and knowledge engineering.

Weight: 551g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030924324
Edition number: 1st ed. 2022