Knowledge engineering : building personal learning assistants for evidence-based reasoning / Gheorghe Tecuci, Dorin Marcu, Mihai Boicu, David Schum.
By: Tecuci, Gheorghe [author.]
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Contributor(s): Marcu, Dorin [author.] | Boicu, Mihai (Infomation scientist) [author.] | Schum, David A [author.].
Material type: 
BookPublisher: New York : Cambridge University Press, 2016Description: 1 online resource (xxiv, 455 pages) : digital, PDF file(s).Content type: text Media type: computer Carrier type: online resourceISBN: 9781316388464 (ebook).Subject(s): Expert systems (Computer science) | Knowledge, Theory of -- Data processing | Computational learning theory | A priori -- Data processingAdditional physical formats: Print version: : No titleDDC classification: 006.3/3 Online resources: Click here to access online Summary: This book presents a significant advancement in the theory and practice of knowledge engineering, the discipline concerned with the development of systems that use expert knowledge and reasoning to solve complex problems. It covers the main stages in the development of a knowledge-based system: understanding the application domain, modeling problem solving in that domain, developing the ontology and the reasoning rules, and testing the system. The book focuses on a special class of systems - learning assistants for evidence-based reasoning that learn complex problem solving expertise directly from human experts, support experts and non-experts in problem solving and decision making, and teach their problem solving expertise to students. A powerful learning agent shell, Disciple-EBR, is included with the book, enabling students, practitioners, and researchers to rapidly develop learning assistants in a wide variety of domains that require evidence-based reasoning, including intelligence analysis, cyber security, law, forensics, medicine, and education.
Title from publisher's bibliographic system (viewed on 06 Sep 2016).
This book presents a significant advancement in the theory and practice of knowledge engineering, the discipline concerned with the development of systems that use expert knowledge and reasoning to solve complex problems. It covers the main stages in the development of a knowledge-based system: understanding the application domain, modeling problem solving in that domain, developing the ontology and the reasoning rules, and testing the system. The book focuses on a special class of systems - learning assistants for evidence-based reasoning that learn complex problem solving expertise directly from human experts, support experts and non-experts in problem solving and decision making, and teach their problem solving expertise to students. A powerful learning agent shell, Disciple-EBR, is included with the book, enabling students, practitioners, and researchers to rapidly develop learning assistants in a wide variety of domains that require evidence-based reasoning, including intelligence analysis, cyber security, law, forensics, medicine, and education.
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