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A new edition of the widely used guide to the key ideas, languages, and technologies of the Semantic Web The development of the Semantic Web, with machine-readable content, has the potential to revolutionize the World Wide Web and its uses. A Semantic Web Primer provides an introduction and guide to this continuously evolving field, describing its key ideas, languages, and technologies. Suitable for use as a textbook or for independent study by professionals, it concentrates on undergraduate-level fundamental concepts and techniques that will enable readers to proceed with building applications on their own and includes exercises, project descriptions, and annotated references to relevant online materials. The third edition of this widely used text has been thoroughly updated, with significant new material that reflects a rapidly developing field. Treatment of the different languages (OWL2, rules) expands the coverage of RDF and OWL, defining the data model independently of XML and including coverage of N3/Turtle and RDFa. A chapter is devoted to OWL2, the new W3C standard. This edition also features additional coverage of the query language SPARQL, the rule language RIF and the possibility of interaction between rules and ontology languages and applications. The chapter on Semantic Web applications reflects the rapid developments of the past few years. A new chapter offers ideas for term projects. Additional material, including updates on the technological trends and research directions, can be found at http://www.semanticwebprimer.org.
The Semantic Web is a new area of research and development in the field of computer science that aims to make it easier for computers to process the huge amount of information on the web, and indeed other large databases, by enabling them not only to read, but also to understand the information. Based on successful courses taught by the authors, and liberally sprinkled with examples and exercises, this comprehensive textbook describes not only the theoretical issues underlying the Semantic Web, but also algorithms, optimisation ideas and implementation details. The book will therefore be valuable to practitioners as well as students, indeed to anyone who is interested in Internet technology, knowledge engineering or description logics. Supplementary materials available online include the source code of program examples and solutions to selected exercises.
The objective of this state-of-the-art survey is to give a coherent overview of the main topics and results achieved by the Network of Excellence REWERSE on 'Reasoning on the Web', funded by the European Commission and Switzerland within the '6th Framework Programme' (FP6), from 2004 to 2008. The material has been organized into eight chapters, each of which addresses one of the main topics of REWERSE: hybrid reasoning with rules and ontologies, lessons in versatility or how query languages adapt to the Web, evolution and reactivity in the Semantic Web, rule-based policy representations and reasoning, component models for Semantic Web languages, controlled English for reasoning on the Semantic Web, semantic search with GoPubMed, and information integration in bioinformatics with ontologies and standards. Each chapter gives an in-depth coverage of the subject and provides an extensive bibliography with pointers to further literature.
Even though the semantic Web is a relatively new and dynamic area of research, a whole suite of components, standards, and tools have already been developed around it. Using a concrete approach, Introduction to the Semantic Web and Semantic Web Services builds a firm foundation in the concept of the semantic Web, its principal technologies, its rea
Dealing with visualization of the second-generation Web, this text presentsresearch on topics such as: visualization of semantic information and metadata;querying XML documents; topic map visualization; visual modelling of XML/RDFontologies; e-commerce and Web search applications; and more.
Optimize Your Sites for Today's Radically New Semantic Search Breakthrough "semantic search" techniques are already transforming Google(tm)'s search results. If you want to be found, yesterday's SEO techniques won't cut it anymore. Google Semantic Search tells you what to do instead--in plain English. David Amerland demystifies Knowledge Graph(tm), TrustRank(tm), AuthorityRank(tm), personalized and mobile search, social media activity, and much more. Drawing on deep knowledge of Google's internal workings and newest patents, he also reveals the growing impact of social networks on your SEO performance. Whether you do it yourself or supervise an agency, this is your complete playbook for next-generation SEO! * Learn how Google is delivering answers, not just links--and what it means to you * Profit from Google Now(tm) and the fragmented, personalized future of search * Prepare for Knowledge Graph(tm) by growing your online reputation, authority, and trust * Stop using 10 common SEO techniques that no longer work * Discover the truth about Trust Ranking(tm)--and 10 steps to take right now * Go way beyond keywords in today's new era of content marketing * Strengthen the "social signal" you create on Twitter, Facebook, Google+, and LinkedIn * See why the "First Page of Google" is rapidly become obsolete * Drive unprecedented business value from your online identity and influence * Learn how Google captures meaning in unstructured data--and give it what it wants * Plan for all "4 Vs" of semantic search: Volume, Velocity, Variety, and Veracity * Rapidly transition from technical to strategic search optimization http://helpmyseo.com/google-semantic-search.html
Ontology Learning for the Semantic Web explores techniques for applying knowledge discovery techniques to different web data sources (such as HTML documents, dictionaries, etc.), in order to support the task of engineering and maintaining ontologies. The approach of ontology learning proposed in Ontology Learning for the Semantic Web includes a number of complementary disciplines that feed in different types of unstructured and semi-structured data. This data is necessary in order to support a semi-automatic ontology engineering process. Ontology Learning for the Semantic Web is designed for researchers and developers of semantic web applications. It also serves as an excellent supplemental reference to advanced level courses in ontologies and the semantic web.
With this book, the promise of the Semantic Web -- in which machines can find, share, and combine data on the Web -- is not just a technical possibility, but a practical reality Programming the Semantic Web demonstrates several ways to implement semantic web applications, using current and emerging standards and technologies. You'll learn how to incorporate existing data sources into semantically aware applications and publish rich semantic data. Each chapter walks you through a single piece of semantic technology and explains how you can use it to solve real problems. Whether you're writing a simple mashup or maintaining a high-performance enterprise solution,Programming the Semantic Web provides a standard, flexible approach for integrating and future-proofing systems and data. This book will help you: Learn how the Semantic Web allows new and unexpected uses of data to emerge Understand how semantic technologies promote data portability with a simple, abstract model for knowledge representation Become familiar with semantic standards, such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL) Make use of semantic programming techniques to both enrich and simplify current web applications
The author looks at the construction of the Semantic Web, which enables computers to automatically and independently consume Web-based information.
The large-scale and almost ubiquitous availability of information has become as much of a curse as it is a blessing. The more information is available, the harder it is to locate any particular piece of it. And even when it has been successfully found, it is even harder still to usefully combine it with other information we may already possess. This problem occurs at many different levels, ranging from the overcrowded disks of our own PCs to the mass of unstructured information on the World Wide Web.It is commonly understood that this problem of information sharing can only be solved by giving computers better access to the semantics of the information. While it has been recognized that ontologies play a crucial role in solving the open problems, most approaches rely on the existence of well-established data structures. To overcome these shortcomings, Stuckenschmidt and van Harmelen describe ontology-based approaches for resolving semantic heterogeneity in weakly structured environments, in particular the World Wide Web. Addressing problems like missing conceptual models, unclear system boundaries, and heterogeneous representations, they design a framework for ontology-based information sharing in weakly structured environments like the Semantic Web.For researchers and students in areas related to the Semantic Web, the authors provide not only a comprehensive overview of the State of the art, but also present in detail recent research in areas like ontology design for information integration, metadata generation and management, and representation and management of distributed ontologies. For professionals in areas such as e-commerce (e.g., the exchange of product knowledge) and knowledge management (e.g., in large and distributed organizations), the book provides decision support on the use of novel technologies, information about potential problems, and guidelines for the successful application of existing technologies.