Recording knowledge in a common framework that would make it possible to seamlessly share global knowledge remains an important challenge for researchers. This brief examines several ideas about the representation of knowledge addressing this challenge. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts. A separate chapter is dedicated to each of the three introduced topics, following a uniform outline: definition, organization, and use. This brief is intended for those who want to get to know the field of knowledge representation quickly, or would like to be up to date with current developments in the field. It is also useful for those dealing with implementation as examples of numerous operational systems are also given.

Based on author's thesis from the Dutch Research School for Information and Knowledge Systems.

Knowledge Representation plays an essential role in Semantic Web, in particular in automated information processing and communications among software agents. This book, entitled "Fuzzy Computational Ontologies in Contexts: Formal Models of Knowledge Representation with Membership Degree and Typicality, and Their Applications", discusses knowledge representation in Semantic Web. It introduces the relevant background knowledge, models of fuzzy ontologies, importance and priority of properties in concepts, and object typicality in fuzzy ontologies and context-aware ontologies. The book is intended for graduate students, engineers, and researchers in the field of artificial intelligence and computer science. Yi Cai is an Assistant Professor in School of Software Engineering, South China University of Technology, Guangzhou, China. Ching-man Au Yeung is a Senior Engineer in Hong Kong Applied Science and Technology Research Institute, Hong Kong, China. Ho-fung Leung is a Professor and the Chairman of Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China.

In this volume, Rudi Studer and his team deliver a self-contained compendium about the exciting field of Semantic Web services, starting with the basic standards and technologies and also including advanced applications in eGovernment and eHealth. The contributions provide both the theoretical background and the practical knowledge necessary to understand the essential ideas and to design new cutting-edge applications.

Ontologies have become increasingly important as the use of knowledge graphs, machine learning, natural language processing (NLP), and the amount of data generated on a daily basis has exploded. As of 2014, 90% of the data in the digital universe was generated in the two years prior, and the volume of data was projected to grow from 3.2 zettabytes to 40 zettabytes in the next six years. The very real issues that government, research, and commercial organizations are facing in order to sift through this amount of information to support decision-making alone mandate increasing automation. Yet, the data profiling, NLP, and learning algorithms that are ground-zero for data integration, manipulation, and search provide less than satisfactory results unless they utilize terms with unambiguous semantics, such as those found in ontologies and well-formed rule sets. Ontologies can provide a rich "schema" for the knowledge graphs underlying these technologies as well as the terminological and semantic basis for dramatic improvements in results. Many ontology projects fail, however, due at least in part to a lack of discipline in the development process. This book, motivated by the Ontology 101 tutorial given for many years at what was originally the Semantic Technology Conference (SemTech) and then later from a semester-long university class, is designed to provide the foundations for ontology engineering. The book can serve as a course textbook or a primer for all those interested in ontologies.

Ontological Engineering refers to the set of activities that concern the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. During the last decade, increasing attention has been focused on ontologies and Ontological Engineering. Ontologies are now widely used in Knowledge Engineering, Artificial Intelligence and Computer Science; in applications related to knowledge management, natural language processing, e-commerce, intelligent integration information, information retrieval, integration of databases, b- informatics, and education; and in new emerging fields like the Semantic Web. Primary goals of this book are to acquaint students, researchers and developers of information systems with the basic concepts and major issues of Ontological Engineering, as well as to make ontologies more understandable to those computer science engineers that integrate ontologies into their information systems. We have paid special attention to the influence that ontologies have on the Semantic Web. Pointers to the Semantic Web appear in all the chapters, but specially in the chapter on ontology languages and tools.

The main purpose of this book is to sum up the vital and highly topical research issue of knowledge representation on the Web and to discuss novel solutions by combining benefits of folksonomies and Web 2.0 approaches with ontologies and semantic technologies. The book contains an overview of knowledge representation approaches in past, present and future, introduction to ontologies, Web indexing and in first case the novel approaches of developing ontologies.