Computational Techniques for Intelligence Analysis: A Cognitive Approach

This book focuses on the definition and implementation of data-driven computational tools supporting decision-making along heterogeneous intelligence scenarios. Intelligence analysis includes methodologies, activities, and tools aimed at obtaining complex information from a set of isolated data gathered from different sensors. The tools aim at increasing the level of situation awareness of decision-makers through the construction of abstract structures supporting human operators in reasoning and making decisions. This book appeals to students, professionals, and academic researchers in computational intelligence and approximate reasoning applications. It is a comprehensive textbook on the subject, supported with case studies and practical examples in Python. The readers will learn how to define decision support systems for the intelligence analysis through the application of situation awareness and granular computing for information processing. 

• Editor-in-Chief and Founder of the international journal “Ambient Intelligence and Humanized Computing,” Springer

• Editor-in-Chief of the international magazine "Evolutionary Intelligence," Springer

• Editor Responsible for Special Issues of the international magazine “Soft Computing,” Springer

• Co-Editor-in-Chief of the international journal "Information Processing Systems"

Francesco Orciuoli received the master’s degree cum laude in computer science from the University of Salerno, Fisciano, Italy. He is an associate professor of computer science with the University of Salerno. His scientific activity, since the beginning of his career, is aimed at defining methods and techniques for supporting human cognitive processes (learning, decision making, reasoning and problem solving). In this regard, in recent years, he is investigating how the paradigms of granular computing (implemented with methods for approximate reasoning such as, for example, probabilistic rough set theory) and cognitive computing (e.g., three-way decisions) can be applied in synergy with other computational approaches to offer an adequate formal framework for human–data interaction applied to different domains such as, for example, intelligence, surveillance, emergency management. He is a co-author of more than 130 scientific publications indexed by SCOPUS, a co-founder of a university spin-off involved in several R&D project related to e-Health and a co-author of a patent in the e-health sector. He is a member of the IEEE and the IEEE Computational Intelligence Society. He is an associate editor of the International Journal of Big Data Intelligence (IJBDI) and serves as a reviewer for numerous international journals such as knowledge-based systems (Elsevier) and IEEE Transactions on Cybernetics and Applied Intelligence (Springer).

Angelo Gaeta received the master’s degree cum laude in electronic engineering and Ph.D. degree in Management and Information Technology from the University of Salerno, Fisciano, Italy. He is currently a research assistant in computer science at the University of Salerno. His research interests relate to situation awareness, approximate reasoning and computational intelligence for decision making and intelligence analysis. He is a co-author of more than 50 scientific publications indexed by SCOPUS on these topics. He is an associate editor of the International Journal Ambient Intelligence and Humanized Computing (Springer) and serves as a reviewer of several international journals.