Knowledge Management and Engineering with Decisional DNA

Lieferzeit: Lieferbar innerhalb 14 Tagen

106,99 

Intelligent Systems Reference Library 183

ISBN: 3030396037
ISBN 13: 9783030396039
Herausgeber: Edward Szczerbicki/Cesar Sanin
Verlag: Springer Verlag GmbH
Umfang: xvi, 248 S., 22 s/w Illustr., 91 farbige Illustr., 248 p. 113 illus., 91 illus. in color.
Erscheinungsdatum: 05.02.2021
Auflage: 1/2020
Produktform: Kartoniert
Einband: KT

This is the first book on experience-based knowledge representation and knowledge management using the unique Decisional DNA (DDNA) technology. The DDNA concept is roughly a decade old, and is rapidly attracting increasing attention and interest among researchers and practitioners. This comprehensive book provides guidelines to help readers develop experience-based tools and approaches for smart engineering of knowledge, data and information. It does not attempt to offer ultimate answers, but instead presents ideas and a number of real-world case studies to explore and exemplify the complexities and challenges of modern knowledge engineering issues. It also increases readers‘ awareness of the multifaceted interdisciplinary character of such issues to enable them to consider – in different ways – developing, evaluating, and supporting smart knowledge engineering systems that use DDNA technology based on experience.

Artikelnummer: 591253 Kategorie:

Beschreibung

This is the first book on experience-based knowledge representation and knowledge management using the unique Decisional DNA (DDNA) technology. The DDNA concept is roughly a decade old, and is rapidly attracting increasing attention and interest among researchers and practitioners. This comprehensive book provides guidelines to help readers develop experience-based tools and approaches for smart engineering of knowledge, data and information. It does not attempt to offer ultimate answers, but instead presents ideas and a number of real-world case studies to explore and exemplify the complexities and challenges of modern knowledge engineering issues. It also increases readers' awareness of the multifaceted interdisciplinary character of such issues to enable them to consider - in different ways - developing, evaluating, and supporting smart knowledge engineering systems that use DDNA technology based on experience.

Autorenporträt

Prof. Edward Szczerbicki has had very extensive experience in the area of intelligent systems development over an uninterrupted 40 year period, 30 years of which he spent in the top systems research centres in the USA, UK, Germany, and Australia. In this area he contributed to the understanding of information and knowledge engineering in systems operating in environments characterized by informational uncertainties and dynamics. He has published 300+ refereed papers, which attracted close to 2500 citations over the last ten years. His DSc degree (1993) and the Title of Professor (2006) were gained in the area of information science for his international published contributions. The research of prof. Szczerbicki contributes significantly to the area of smart knowledge engineering and development of intelligent systems. His academic experience includes positions with Gdansk University of Technology, Gdansk, Poland; Strathclyde University, Glasgow, Scotland; The University of Iowa, Iowa City, USA; University of California, Berkeley, USA; and The University of Newcastle, Newcastle, Australia. Dr. Cesar Sanin counts with extensive experience in the development of knowledge engineering and intelligent technologies for the past 17 years. He gained studies in the Bachelor of Systems Engineering from EAFIT University, Colombia; Administrative Engineering from the National University of Colombia; and an IT Diploma at The University of Newcastle, Australia. Afterwards, he pursued a PhD degree at the School of Engineering of The University of Newcastle and received his degree in the field of Knowledge Engineering and Intelligent Technologies (2007). Currently, he continues his work at The University of Newcastle as a co-director of the Knowledge Engineering Research Team - KERT, where he mainly contributes to the expansion and use of knowledge engineering, decision support systems and intelligent systems for engineering and business.

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