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Corporate Knowledge Discovery and Organizational Learning: The Role, Importance, and Application of Semantic Business Process Management: Knowledge Management and Organizational Learning, cartea 2

Editat de András Gábor, Andrea Kő
en Limba Engleză Hardback – 26 apr 2016
This book investigates organizational learning from a variety ofinformation processing perspectives. Continuous change and complexity inregulatory, social and economic environments are increasingly forcingorganizations and their employees to acquire the necessary job-specificknowledge at the right time and in the right format. Though many regulatorydocuments are now available in digital form, their complexity and diversitymake identifying the relevant elements for a particular context a challenging task.In such scenarios, business processes tend to be important sources ofknowledge, containing rich but in many cases embedded, hidden knowledge.
This book discusses the possible connection between businessprocess models and corporate knowledge assets; knowledge extraction approachesbased on organizational processes; developing and maintaining corporateknowledge bases; and semantic business process management and its relation toorganizational learning approaches. Theindividual chapters reveal the differentelements of a knowledge management solution designed to extract, organize andpreserve the knowledge embedded in business processes so as to: enrichorganizational knowledge bases in a systematic and controlled way, supportemployees in acquiring job role-specific knowledge, promote organizationallearning, and steer human capital investment. All of these topics are analyzedon the basis of real-world cases from the domains of insurance, food safety,innovation, and funding.
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Specificații

ISBN-13: 9783319289151
ISBN-10: 3319289152
Pagini: 200
Ilustrații: XI, 173 p. 71 illus., 62 illus. in color.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.44 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Knowledge Management and Organizational Learning

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Corporate Knowledge Discovery and Organizational Learning - The Role, Importance, and Application of Semantic Business Process Management - The ProKEX Case.- Corporate Semantic Business Process Management.- ProMine: A Text Mining Solution for Concept Extraction and Filtering.- STUDIO - Ontology-Centric Knowledge-Based System.- Ontology Tailoring for Job Role Knowledge.- STUDIO: A Solution on Adaptive Testing.- Future Development: Towards Semantic Compliance Checking.

Notă biografică

Dr. András Gábor is director of Institute of Informatics and professor of Department of Information Systems at the Corvinus University of Budapest, research director of Corvinno Technology Transfer Ltd. He earned a diploma (MSc) in Business and Economics (1974), and  in Computer Science  (1979), dr. univ. oec.  (1976), CSc (Ph.D) (1983), CISA (1999), habil.dr (2002). His expertise spans systems analysis, process management, information management, intelligent systems. He leads several national and international research projects and is the author of prominent Hungarian and international publications. He was visiting scholar at DePaul University, Chicago, Imperial College, London,  and at the University of Amsterdam. Besides academic activities, he was a consultant for the Inter-ministerial Committee for IT and the Modernization and Integration Project Office, 1990-98. Between 2003-2006 worked as a consultant on behalf of the Ministry of Educationconcerning MIS development in Higher Education.
Andrea Kő, PhD, Habil, CISA is an Associate Professor of Corvinus University of Budapest, Department of Information Systems. She has a University Doctoral degree in Computer Science (1992) from Corvinus University of Budapest, Hungary and a PhD degree in Management and Business Administration (2005) from Corvinus University of Budapest, Hungary. She participated in several international and national research projects in the areas of: intelligent systems, knowledge management; semantic technologies and e-government. She has published more than 80 papers in international scientific journals and conferences. Her research interests include: intelligent systems, business intelligence, knowledge management, and semantic technologies. 

Textul de pe ultima copertă

This book investigates organizational learning from a variety of information processing perspectives. Continuous change and complexity in regulatory, social and economic environments are increasingly forcing organizations and their employees to acquire the necessary job-specific knowledge at the right time and in the right format. Though many regulatory documents are now available in digital form, their complexity and diversity make identifying the relevant elements for a particular context a challenging task. In such scenarios, business processes tend to be important sources of knowledge, containing rich but in many cases embedded, hidden knowledge.
This book discusses the possible connection between business process models and corporate knowledge assets; knowledge extraction approaches based on organizational processes; developing and maintaining corporate knowledge bases; and semantic business process management and its relation to organizational learning approaches. The individual chapters reveal the different elements of a knowledge management solution designed to extract, organize and preserve the knowledge embedded in business processes so as to: enrich organizational knowledge bases in a systematic and controlled way, support employees in acquiring job role-specific knowledge, promote organizational learning, and steer human capital investment. All of these topics are analyzed on the basis of real-world cases from the domains of insurance, food safety, innovation, and funding.

Caracteristici

Provides a new way to knowledge discovery and extraction from business processes Introduces ontology-based adaptive testing and learning Illustrates the elicited methodology through three different applicable cases Includes supplementary material: sn.pub/extras