This book constitutes the refereed proceedings of the 12th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2000, held in Juan-les-Pins, France in October 2000. The 28 revised full papers and six revised short papers presented were carefully reviewed and selected from a high number of high-quality submissions. The book offers topical sections on knowledge modeling languages and tools, ontologies, knowledge acquisition from texts, machine learning, knowledge management and electronic commerce, problem solving methods, knowledge representation, validation, evaluation and certification, and methodologies.

The disciplines of knowledge engineering and knowledge management are closely tied. Knowledge engineering deals with the development of information systems in which knowledge and reasoning play pivotal roles. Knowledge management, a newly developed field at the intersection of computer science and management, deals with knowledge as a key resource in modern organizations. Managing knowledge within an organization is inconceivable without the use of advanced information systems; the design and implementation of such systems pose great organization as well as technical challenges.

Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.

Knowledge Management and Organizational Memories presents models, methods, and techniques for building, managing and using corporate memories. These models incorporate knowledge bases, ontologies, documents, FAQs, workflow systems, case-based reasoning systems, multi-agent systems, and CSCW. The book is divided into five parts: methods; knowledge-based approaches; ontologies and documents; case-based reasoning approaches; and distributed and collaborative approaches.