Managing Knowledge With Artificial Intelligence

In clear, readable language, consultant and researcher Kevin Desouza accomplishes an unlikely feat: explaining artificial intelligence to nonspecialists, in a way that experts will recognize and accept as correct and immediately applicable. Workers in knowledge management are relatively isolated from each other, businesspeople are still unconvinced that artificial intelligence has much to offer, and engineers creating the latest algorithm or device seldom consider its value for businesspeople—Desouza seeks to change all that. He maintains that knowledge will be traded like physical goods, and that businesses must leverage knowledge resources within its organizations to survive in a highly competitive marketplace. Introducing us the concepts and significance of knowledge management, he shows that incorporating artificial intelligence computer-based techniques into business settings can provide truly significant gains in productivity. This book is among the first of its kind to provide a comprehensive one-stop guide to the basics of knowledge management, plus a lucid explanation of A.I., and how to use it in almost all types of organizational settings.

This book features a selection of extended papers presented at the 8th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2021, held in Yokohama, Japan, in January 2021, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2020.* The 14 revised and extended papers presented together with an invited talk were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management and discuss methodological, technical and organizational aspects of artificial intelligence used for knowledge management. *The workshop was held virtually.

A framework for knowledge management continues to elude the community, and relabeling a variety of methods, technologies, and fields of practice as knowledge management confounds the issue. This revised text identifies three subdomains, eight disciplines, and seven core competencies.

Knowledge Management: Systems and Processes in the AI Era, Third Edition, is aimed at students and managers who seek detailed insights into contemporary knowledge management (KM). It explains the concepts, theories, and technologies that provide the foundation for knowledge management; the systems and structures that constitute KM solutions; and the processes for developing, deploying, and evaluating these KM solutions. This book serves as a complete introduction to the subject of knowledge management, incorporating technical and social aspects, as well as concepts, practical examples, traditional KM approaches, and emerging topics. This third edition has been revised and expanded to include more coverage of emergent trends such as cloud computing, online communities, crowdsourcing, and artificial intelligence. Aimed at advanced undergraduate, postgraduate, and MBA students who are seeking a comprehensive perspective on knowledge management, Knowledge Management is also complemented by online support for lecturers including suggested solutions to the many review questions and application exercises contained within the book.

Current experimental systems in industry, government, and the military take advantage of knowledge-based processing. For example, the Defense Advanced Research Projects Agency (DARPA), and the United States Geological Survey (USGS) are supporting the develop ment of information systems that contain diverse, vast, and growing repositories of data (e.g., vast databases storing geographic informa tion). These systems require powerful reasoning capabilities and pro cessing such as data processing, communications, and multidisciplinary of such systems will scientific analysis. The number and importance grow significantly in the near future. Many of these systems are severely limited by current knowledge base and database systems technology. Currently, knowledge-based system technology lacks the means to provide efficient and robust knowledge bases, while database system technology lacks knowledge representation and reasoning capabilities. The time has come to face the complex research problems that must be solved before we can design and implement real, large scale software systems that depend on knowledge-based processing. To date there has been little research directed at integrating knowledge base and database technologies. It is now imperative that such coordinated research be initiated and that it respond to the urgent need for a tech nology that will enable operational large-scale knowledge-based system applications.

This book constitutes the refereed proceedings of the 8th International Conference On Secure Knowledge Management In Artificial Intelligence Era, SKM 2019, held in Goa, India, in December 2019. The 12 full papers presented were carefully reviewed and selected from 34 submissions. They were organized according to the following topical sections: cyber security; security and artifcial intelligence; access control models; and social networks.

For knowledge management to be successful, the corporate culture needs to be adapted to encourage the creation, sharing, and distribution of knowledge within the organization. Knowledge Organizations: What Every Manager Should Know provides insight into how organizations can best accomplish this goal. Liebowitz and Beckman provide the information companies need for evaluating and planning the steps and processes that will transform their existing organization infrastructure into a "knowledge-based" organization. This easy-to-read guide includes many vignettes, examples, and short cases of organizations involved in knowledge management.

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 enh