Name: Knowledge Management: Learning From Knowledge Engineering (en Inglés)
Price: 212.77 PEN
Availability: InStock
Author: Jay Liebowitz
ISBN: 9780367455316

portada Knowledge Management: Learning From Knowledge Engineering (en Inglés)

Formato

Libro Físico

Editorial

Crc Press

Autor

Jay Liebowitz

Idioma

Inglés

N° páginas

152

Encuadernación

Tapa Blanda

ISBN13

9780367455316

N° edición

Knowledge Management: Learning From Knowledge Engineering (en Inglés)

Jay Liebowitz (Autor) · Crc Press · Tapa Blanda

Libro Nuevo

S/ 212,77

S/ 425,54

Ahorras: S/ 212,77

50% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Viernes 05 de Julio y el Martes 23 de Julio.

Lo recibirás en cualquier lugar de Perú entre 2 y 5 días hábiles luego del envío.

Reseña del libro "Knowledge Management: Learning From Knowledge Engineering (en Inglés)"

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.