Knowledge Representation Practionary

This major work on knowledge representation is based on the writings of Charles S. Peirce, a logician, scientist, andphilosopher of the first rank at the beginning of the 20th century.This book follows Peirce's practical guidelines and universal categories in a structuredapproach to knowledge representation that captures differences in events,entities, relations, attributes, types, and concepts. Besides the ability tocapture meaning and context, the Peircean approach is also well-suited tomachine learning and knowledge-based artificial intelligence. Peirce is a founder of pragmatism, the uniquely American philosophy. Knowledge representation is shorthand for how to represent humansymbolic information and knowledge to computers to solve complexquestions. KR applications range from semantic technologies andknowledge management and machine learning to information integration,data interoperability, and natural language understanding. Knowledgerepresentation is an essential foundation for knowledge-based AI. This book is structured into five parts. The first and last parts are bookendsthat first set the context and background and conclude with practicalapplications. The three main parts that are the meat of the approach firstaddress the terminologies and grammar of knowledge representation, thenbuilding blocks for KR systems, and then design, build, test, and bestpractices in putting a system together. Throughout, the book refers to andleverages the open source KBpedia knowledge graph and its publicknowledge bases, including Wikipedia and Wikidata. KBpedia is a readybaseline for users to bridge from and expand for their own domain needsand applications. It is built from the ground up to reflect Peirceanprinciples. This book is one of timeless, practical guidelines for how to think about KRand to design knowledge management (KM) systems. The book isgrounded bedrock for enterprise information and knowledge managerswho are contemplating a new knowledge initiative. This book is an essential addition to theory and practice for KRand semantic technology and AI researchers and practitioners,who will benefit from Peirce's profound understanding of meaning and context.