By Christopher Walton
This hugely topical textual content considers the development of the subsequent iteration of the internet, known as the Semantic internet. it will permit pcs to instantly devour Web-based details, overcoming the human-centric concentration of the internet because it stands at the moment, and expediting the development of a complete new type of knowledge-based functions that would intelligently make the most of internet content.
The textual content is dependent into 3 major sections on wisdom illustration thoughts, reasoning with multi-agent structures, and data companies. for every of those themes, the textual content offers an summary of the state of the art concepts and the preferred criteria which have been outlined. a variety of small programming examples are given, which exhibit how the advantages of the Semantic internet applied sciences might be discovered this present day. the most theoretical effects underlying all the applied sciences are offered, and the most difficulties and learn matters which stay are summarized.
Based on a path on 'Multi-Agent structures and the Semantic net' taught on the college of Edinburgh, this article is perfect for final-year undergraduate and graduate scholars in arithmetic, computing device technology, man made Intelligence, and good judgment and researchers attracted to Multi-Agent platforms and the Semantic net
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Additional resources for Agency and the Semantic Web
Van de Velde, and B. Wielinga. Knowledge Engineering and Management: The CommonKADS Methodology. MIT Press, 1999. 12. K. Sycara and M. Paolucci. Ontologies in Agent Architectures. In Handbook on Ontologies in Information Systems. Springer-Verlag, 2004. 13. M. Uschold and M. Gruninger. Ontologies: Principles, Methods, and Applications. Knowledge Engineering Review, 11(2): 93–155, June 1996. 2 Web knowledge In the introductory chapter of this book, we discussed the means by which knowledge can be made available on the Web.
Therefore, we introduce the main concepts of RDF in a more concise manner before discussing how these concepts are represented in XML syntax. The key to knowledge representation is expressing the structure of the information that we want to represent. For example, representing the relationships between the different components of a camera. As we have shown previously, this structure can be represented graphically as a network. To understand RDF, it is useful to view the syntax as simply a textual representation of a graph.
R. Gruber. Towards Principles for the Design of Ontologies Used for Knowledge Sharing. Kluwer, 1993. 9. J. Hendler. Is There an Intelligent Agent in Your Future? Nature—Web Matters, (3), March 1999. 10. J. Hendler. Agents on the Web. IEEE Intelligent Systems, 16(2): 30–7, March 2001. 11. G. Schreiber, H. Akkermans, A. Anjewierden, R. de Hoog, N. Shadbolt, W. Van de Velde, and B. Wielinga. Knowledge Engineering and Management: The CommonKADS Methodology. MIT Press, 1999. 12. K. Sycara and M. Paolucci.