Relational Calculus for Actionable Knowledge

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.

本書專注於新興科學領域「資料科學」所面臨的一個主要挑戰：將資料轉化為可行動的知識，以利用不斷增加的資料量並應對其固有的複雜性。可行動的知識在管理、商業和社會科學領域已經得到了定性和深入的研究，但在計算機科學和工程領域，它與數據挖掘及其演進「知識發現和數據挖掘」（KDD）的聯繫直到最近才建立起來。數據挖掘旨在從數據中提取有趣的模式，但迄今為止，從數據中發現的模式並不總是對社會技術組織（STO）的決策者具有「可行動性」。隨著互聯網和連接性的發展，STO已經演變成被稱為「網絡物理社會系統」（CPSS）的系統，這些系統被認為描述了我們今天的世界。在這樣複雜且動態的環境中，傳統的KDD過程是不夠的，需要額外的過程將複雜的數據轉化為可行動的知識。

本書向讀者介紹了高級知識概念以及旨在提供可行動的知識的分析和信息融合（AIF）過程。作者們提供了對「關係」概念及其應用的理解，關係演算，以及在AIF過程中實現語義增長的特定知識維度的形式化。本書作為關係演算及其應用於處理鏈以生成可行動的知識的重要技術介紹。它非常適合研究生、研究人員或對決策科學和知識工程感興趣的行業專業人士閱讀。

Dr. Éloi Bossé is a researcher in decision support and analytics and information fusion (AIF). He possesses vast experience in applying his research to defense and security related problems, and, more recently, to civilian domains. He is currently the president of Expertise Parafuse Inc., a consultant firm on AIF and decision-support. He holds an academic position as an associate researcher at IMT-Atlantique in Brest, France and a Ph.D. in electrical engineering from the Université Laval in Québec City, Canada. Dr. Bossé has published 7 books on AIF related topics and over 200 papers in journals, book chapters, conference proceedings, and technical reports

Dr. Michel Barès is an independent researcher in Artificial Intelligence (AI). He was formerly a researcher at DRET (Direction des Recherches Et Technologies) under the French Ministry of Defense. There, he conducted innovative research projects on symbolic reasoning, decision support, and distributed AI and was a pioneer in introducing distributed AI to military command decision-making. In parallel to his military research work, he has acted as professor for several universities and specialized French schools. Since 2017, he has served as a scientific advisor for Expertises Parafuse Inc., a small research firm located in Québec City, Canada. Dr. Barès holds a Ph.D. in mathematics from the Pierre and Marie Curie University in Paris, France. He has published 8 academic books on computer science and AI and more than 150 scientific publications in journals, conference proceedings, and technical reports.

Dr. Éloi Bossé是一位決策支援、分析和資訊融合（AIF）領域的研究員。他在將研究應用於國防和安全相關問題以及最近的民用領域方面擁有豐富的經驗。他目前擔任Expertise Parafuse Inc.的總裁，該公司是一家提供AIF和決策支援顧問服務的顧問公司。他在法國布雷斯特的IMT-Atlantique擔任副研究員職位，並擁有加拿大魁北克市拉瓦爾大學的電機工程博士學位。Bossé博士已經出版了7本關於AIF相關主題的書籍，並在期刊、專書章節、會議論文和技術報告中發表了200多篇論文。

Dr. Michel Barès是一位獨立的人工智慧（AI）研究員。他曾在法國國防部的DRET（研究與技術指導局）擔任研究員。在那裡，他進行了關於符號推理、決策支援和分散式AI的創新研究項目，並在將分散式AI引入軍事指揮決策方面是一位先驅者。除了軍事研究工作外，他還擔任多所大學和專業法國學校的教授。自2017年以來，他擔任加拿大魁北克市一家名為Expertises Parafuse Inc.的小型研究公司的科學顧問。Barès博士擁有巴黎皮埃爾和瑪麗居里大學的數學博士學位。他已經出版了8本關於計算機科學和AI的學術書籍，並在期刊、會議論文和技術報告中發表了150多篇科學論文。