Intelligence Semantics

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By Christopher Walton

This hugely topical textual content considers the development of the subsequent new release of the net, referred to as the Semantic net. this may allow desktops to instantly devour Web-based info, overcoming the human-centric concentration of the internet because it stands at the moment, and expediting the development of an entire new type of knowledge-based purposes that might intelligently make the most of internet content.

The textual content is established into 3 major sections on wisdom illustration concepts, reasoning with multi-agent platforms, and data prone. for every of those subject matters, the textual content presents an summary of the cutting-edge concepts and the preferred criteria which were outlined. quite a few small programming examples are given, which display how some great benefits of the Semantic internet applied sciences could be learned this day. the most theoretical effects underlying all of the applied sciences are awarded, and the most difficulties and study concerns which stay are summarized.
Based on a path on 'Multi-Agent structures and the Semantic internet' taught on the college of Edinburgh, this article is perfect for final-year undergraduate and graduate scholars in arithmetic, computing device technological know-how, synthetic Intelligence, and good judgment and researchers drawn to Multi-Agent platforms and the Semantic net

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Extra resources for Agency and the Semantic Web

Example text

The following example expresses the statement ‘Photomart says that the D70 is manufactured by Nikon’. Note that we define an rdf:Statement rather than a description. We explicitly define the subject, predicate, and object that we are talking about. 6. 6 RDF reification. 2 RDF schema vocabularies At the beginning of the chapter, we discussed two tasks that are key to the representation of knowledge on the Semantic Web. To recap, we define ontologies that provide structure to the knowledge, and we construct knowledge bases according to these ontologies that hold the knowledge.

The alternative is to use an XML entity declaration, as shown in line 3 of the example. An entity associates a name with a string, and substitutes this name for the string when used within the document. org/2001/XMLSchema#. The name is substituted for the string in line 12 when we write &xsd; and in this way obtain the correct type in our example. RDF permits the definition of network nodes that do not contain resources, by using blank node identifiers. In line 16, we define a blank node using the rdf:nodeID attribute, and in line 14 we refer to this node using the alt ID that we assigned to the node.

We indicate the domain and range of the properties with D and R respectively. g. the root of the RDF class hierarchy is the rdfs:Resource class. A number of additional RDFS properties are used in these definition documents, primarily to make them more human-readable. The rdfs:comment property provides a description of a resource, and the rdfs:label property provides an alternative (informal) labelling scheme. g. in a text document. 3 The web ontology language The RDFS approach to defining RDF vocabularies is limited in expressibility.

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