Relational Calculus for Actionable Knowledge / by Michel Barès, Éloi Bossé.

Format:

Book

Author/Creator:

Barès, Michel, Author.

Bossé, Éloi., Author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Information Fusion and Data Science, 2510-1536

Language:

English

Subjects (All):

Artificial intelligence-Data processing.

Coding theory.

Information theory.

Proof theory.

Expert systems (Computer science).

Knowledge, Theory of.

Data Science.

Coding and Information Theory.

Proof Theory and Constructive Mathematics.

Knowledge Based Systems.

Epistemology.

Local Subjects:

Data Science.

Coding and Information Theory.

Proof Theory and Constructive Mathematics.

Knowledge Based Systems.

Epistemology.

Physical Description:

1 online resource (XX, 340 pages) : 142 illustrations, 62 illustrations in color.

Edition:

1st ed. 2022.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

System Details:

text file PDF

Summary:

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. .

Contents:

Chapter1. Introduction to Actionable Knowledge: Concepts and Definitions

Chapter2. Knowledge and its Dimensions

Chapter3. The Knowledge Chain

Chapter4. Preliminaries on Crisp and Fuzzy Relational Calculus

Chapter5. Actionable Knowledge for Efficient Actions

Chapter6. Relational Calculus for the Generation of Actionable Knowledge

Chapter7. Conclusion. .

Other Format:

Printed edition:

ISBN:

978-3-030-92430-0

9783030924300

Access Restriction:

Restricted for use by site license.