Relational Calculus for Actionable Knowledge (Hardcover, 1st ed. 2022)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Information Fusion and Data Science
Release date:	2022
First published:	2022
Authors:	Michel Bares • Eloi Bosse
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	340
Edition:	1st ed. 2022
ISBN-13:	978-3-03-092429-4
Categories:	Books > Reference & Interdisciplinary > Communication studies > Coding theory & cryptology Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Humanities > Philosophy > Topics in philosophy > Epistemology, theory of knowledge Books > Science & Mathematics > Mathematics > Mathematical foundations > Mathematical logic Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems Books > Philosophy > Topics in philosophy > Epistemology, theory of knowledge
LSN:	3-03-092429-7
Barcode:	9783030924294

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