Автор: Michel Bares, Eloi Bosse
Издательство: Springer
Серия: Information Fusion and Data Science
Год: 2022
Страниц: 360
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
This book focuses on one of the major challenges of the newly created scientific domain known as Data Science: turning data into actionable knowledge in order to exploit increasing data volumes and deal with their inherent complexity. Actionable knowledge has been qualitatively and intensively studied in management, business, and the social sciences but in computer science and engineering, its connection has only recently been established to data mining and its evolution, ‘Knowledge Discovery and Data Mining’ (KDD). Data mining seeks to extract interesting patterns from data, but, until now, the patterns discovered from data have not always been ‘actionable’ for decision-makers in Socio-Technical Organizations (STO). With the evolution of the Internet and connectivity, STOs have evolved into Cyber-Physical and Social Systems (CPSS) that are known to describe our world today. In such complex and dynamic environments, the conventional KDD process is insufficient, and additional processes are required to transform complex data into actionable knowledge.
Readers are presented with advanced knowledge concepts and the analytics and information fusion (AIF) processes aimed at delivering actionable knowledge. The authors provide an understanding of the concept of ‘relation’ and its exploitation, relational calculus, as well as the formalization of specific dimensions of knowledge that achieve a semantic growth along the AIF processes. This book serves as an important technical presentation of relational calculus and its application to processing chains in order to generate actionable knowledge. It is ideal for graduate students, researchers, or industry professionals interested in decision science and knowledge engineering.
The book offers four major contributions: (1) the concept of “relation” and its exploitation (relational calculus) for the AIF processes, (2) the formalization of certain dimensions of knowledge to achieve a semantic growth along the AIF processes, (3) the modeling of the interrelations within the couple (knowledge, action) to gain sense, and finally (4) the exploitation of relational calculus to support the AIF core technological processes that allow to transform data into actionable knowledge.
This book addresses two main poles: computations with relations (relational calculus) and creation of actionable knowledge. In the first three chapters, we explore basic properties of knowledge, knowledge representations, and knowledge processes from scientific and practical perspectives emphasizing existing directions and areas in knowledge studies. We also examine the fundamental role of information and define the relationship that exists between data, information, and knowledge. We discuss the need for formalization. Any automatic process geared to support human decision-making must be indeed endowed with reasoning ability, depending on the circumstances and the context of its employment.
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