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.
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.
Social Networks and the Semantic Web offers valuable information to practitioners developing social-semantic software for the Web. It provides two major case studies. The first case study shows the possibilities of tracking a research community over the Web. It reveals how social network mining from the web plays an important role for obtaining large scale, dynamic network data beyond the possibilities of survey methods. The second case study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies.
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.
This major work on knowledge representation is based on the writings of Charles S. Peirce, a logician, scientist, and philosopher of the first rank at the beginning of the 20th century. This book follows Peirce's practical guidelines and universal categories in a structured approach to knowledge representation that captures differences in events, entities, relations, attributes, types, and concepts. Besides the ability to capture meaning and context, the Peircean approach is also well-suited to machine learning and knowledge-based artificial intelligence. Peirce is a founder of pragmatism, the uniquely American philosophy. Knowledge representation is shorthand for how to represent human symbolic information and knowledge to computers to solve complex questions. KR applications range from semantic technologies and knowledge management and machine learning to information integration, data interoperability, and natural language understanding. Knowledge representation is an essential foundation for knowledge-based AI. This book is structured into five parts. The first and last parts are bookends that first set the context and background and conclude with practical applications. The three main parts that are the meat of the approach first address the terminologies and grammar of knowledge representation, then building blocks for KR systems, and then design, build, test, and best practices in putting a system together. Throughout, the book refers to and leverages the open source KBpedia knowledge graph and its public knowledge bases, including Wikipedia and Wikidata. KBpedia is a ready baseline for users to bridge from and expand for their own domain needs and applications. It is built from the ground up to reflect Peircean principles. This book is one of timeless, practical guidelines for how to think about KR and to design knowledge management (KM) systems. The book is grounded bedrock for enterprise information and knowledge managers who are contemplating a new knowledge initiative. This book is an essential addition to theory and practice for KR and semantic technology and AI researchers and practitioners, who will benefit from Peirce's profound understanding of meaning and context.
Continual advancements in web technology have highlighted the need for formatted systems that computers can utilize to easily read and sift through the hundreds of thousands of data points across the internet. Therefore, having the most relevant data in the least amount of time to optimize the productivity of users becomes a priority. Semantic Web Science and Real-World Applications provides emerging research exploring the theoretical and practical aspects of semantic web science and real-world applications within the area of big data. Featuring coverage on a broad range of topics such as artificial intelligence, social media monitoring, and microblogging recommendation systems, this book is ideally designed for IT consultants, academics, professionals, and researchers of web science seeking the current developments, requirements and standards, and technology spaces presented across academia and industries.
This book constitutes the refereed proceedings of the 4th Conference on Knowledge Engineering and the Semantic Web, KESW 2013, held in St. Petersburg, Russia, in October 2013. The 18 revised full papers presented together with 7 short system descriptions were carefully reviewed and selected from 52 submissions. The papers address research issues related to knowledge representation, semantic web, and linked data.
Social Semantics: The Search for Meaning on the Web provides a unique introduction to identity and reference theories of the World Wide Web, through the academic lens of philosophy of language and data-driven statistical models. The Semantic Web is a natural evolution of the Web, and this book covers the URL-based Web architecture and Semantic Web in detail. It has a robust empirical side which has an impact on industry. Social Semantics: The Search for Meaning on the Web discusses how the largest problem facing the Semantic Web is the problem of identity and reference, and how these are the results of a larger general theory of meaning. This book hypothesizes that statistical semantics can solve these problems, illustrated by case studies ranging from a pioneering study of tagging systems to using the Semantic Web to boost the results of commercial search engines. Social Semantics: The Search for Meaning on the Web targets practitioners working in the related fields of the semantic web, search engines, information retrieval, philosophers of language and more. Advanced-level students and researchers focusing on computer science will also find this book valuable as a secondary text or reference book.
Augmented and virtual reality (AR and VR) offer exciting opportunities for human computer interaction (HCI), the enhancement of places, and new business cases. Though VR is most popular for video games, especially among younger generations, AR and VR can also be used in applications that include military, medical, navigational, tourism, marketing, and maintenance uses. Research in these technologies along with 3D user interfaces has gained momentum in recent years and has solidified it as a staple technology for the foreseeable future. Multimedia and Sensory Input for Augmented, Mixed, and Virtual Reality includes a collection of business case studies covering a variety of topics related to AR, VR, and mixed reality (MR) including their use in possible applications. This book also touches on the diverse uses of AR and VR in many industries and discusses their importance, challenges, and opportunities. While discussing the use these technologies in sectors such as education, healthcare, and computer science, this book is ideal for computer scientists, engineers, practitioners, stakeholders, researchers, academicians, and students who are interested in the latest research on augmented, mixed, and virtual reality.
