This conference proceedings investigates the emerging field of knowledge capture, focusing on the methods, tools, and challenges involved in acquiring, representing, and utilizing human expertise within computational systems. The collection presents research from leading figures in artificial intelligence and knowledge management, exploring how to build systems that can learn from and reason with complex information.

This collection of papers from the 1st International Conference on Knowledge Capture offers a snapshot of the field's foundational research at the turn of the millennium. The contributions likely represent a dense, technical exploration of artificial intelligence and knowledge management principles, aimed at researchers and practitioners in computer science. The focus on methods and tools suggests a practical, albeit academic, approach to understanding and building knowledge-intensive systems.