A recent area of interest in the Artificial Intelligence community has been the application of massively parallel algorithms to enhance the choice mechanism in traditional AI problems. This volume provides a detailed description of how marker-passing -- a parallel, non-deductive, spreading activation algorithm -- is a powerful approach to refining the choice mechanisms in an AI problem-solving system.
The author scrutinizes the design of both the algorithm and the system, and then reviews the current literature and research in planning and marker passing. Also included: a comparison of this computer model with some standard cognitive models, and a comparison of this model to the "connectionist" approach.

A Framework for Web Science sets out a series of approaches to the analysis and synthesis of the World Wide Web, and other web-like information structures. A comprehensive set of research questions is outlined, together with a sub-disciplinary breakdown, emphasising the multi-faceted nature of the Web, and the multi-disciplinary nature of its study and development. These questions and approaches together set out an agenda for Web Science, the science of decentralised information systems. Web Science is required both as a way to understand the Web, and as a way to focus its development on key communicational and representational requirements. A Framework for Web Science surveys central engineering issues, such as the development of the Semantic Web, Web services and P2P. Analytic approaches to discover the Web's topology, or its graph-like structures, are examined. Finally, the Web as a technology is essentially socially embedded; therefore various issues and requirements for Web use and governance are also reviewed. A Framework for Web Science is aimed primarily at researchers and developers in the area of Web-based knowledge management and information retrieval. It will also be an invaluable reference for students in computer science at the postgraduate level, academics and industrial practitioners.

After years of mostly theoretical research, Semantic Web Technologies are now reaching out into application areas like bioinformatics, eCommerce, eGovernment, or Social Webs. Applications like genomic ontologies, semantic web services, automated catalogue alignment, ontology matching, or blogs and social networks are constantly increasing, often driven or at least backed up by companies like Google, Amazon, YouTube, Facebook, LinkedIn and others. The need to leverage the potential of combining information in a meaningful way in order to be able to benefit from the Web will create further demand for and interest in Semantic Web research.

This movement, based on the growing maturity of related research results, necessitates a reliable reference source from which beginners to the field can draw a first basic knowledge of the main underlying technologies as well as state-of-the-art application areas. This handbook, put together by three leading authorities in the field, and supported by an advisory board of highly reputed researchers, fulfils exactly this need. It is the first dedicated reference work in this field, collecting contributions about both the technical foundations of the Semantic Web as well as their main usage in other scientific fields like life sciences, engineering, business, or education.