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Knowledge Management (Learning from Knowledge Engineering)
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Product Details
Author:
Jay Liebowitz
Format:
Paperback
Pages:
152
Publisher:
CRC Press (December 2, 2019)
Language:
English
ISBN-13:
9780367455316
Weight:
16oz
Dimensions:
6.125" x 9.1875"
File:
TAYLORFRANCIS-TayFran_260711045735556-20260711.xml
Folder:
TAYLORFRANCIS
List Price:
$86.99
Case Pack:
1
As low as:
$82.64
Publisher Identifier:
P-CRC
Discount Code:
H
Audience:
Professional and scholarly
Country of Origin:
United States
Pub Discount:
30
Imprint:
CRC Press
Overview
Knowledge Management (KM) is strongly rooted in the discipline of Knowledge Engineering (KE), which in turn grew partly out of the artificial intelligence field. Despite their close relationship, however, many KM specialists have failed to fully recognize the synergy or acknowledge the power that KE methodologies, techniques, and tools hold for enhancing the state of the art in Knowledge Management.
Knowledge Management: Learning from Knowledge Engineering addresses this vacuum. It gives concise, practical information and insights drawn from the author's many years of experience in the fields of expert systems and Knowledge Management. Based upon research, analyses, and illustrative case studies, this is the first book to integrate the theory and practice of artificial intelligence and expert systems with the current organizational and strategic aspects of Knowledge Management.
The time has come for Knowledge Management professionals to appreciate the synergy between their work and the work of their counterparts in Knowledge Engineering. Knowledge Management: Learning from Knowledge Engineering is the ideal starting point for those in KM to learn from and exploit advances in that field, and thereby advance their own.
Knowledge Management: Learning from Knowledge Engineering addresses this vacuum. It gives concise, practical information and insights drawn from the author's many years of experience in the fields of expert systems and Knowledge Management. Based upon research, analyses, and illustrative case studies, this is the first book to integrate the theory and practice of artificial intelligence and expert systems with the current organizational and strategic aspects of Knowledge Management.
The time has come for Knowledge Management professionals to appreciate the synergy between their work and the work of their counterparts in Knowledge Engineering. Knowledge Management: Learning from Knowledge Engineering is the ideal starting point for those in KM to learn from and exploit advances in that field, and thereby advance their own.








