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We are exploring the use of fuzzy data mining and concepts introduced by the semanticweb to operate in synergy to perform distributed intrusion detection.
Most of the required means for expressing configuration knowledge are already provided by current versions of semanticweb knowledge representation languages.
The promise of the semanticweb is that it will remove a lot of that slog.
Most studies have focused on the employment of monotonic logics in the layered development of the semanticweb.
Notions of a 'semanticweb' or of 'data mining' depend on these dynamic functions becoming quicker and more reliable.
Ontologies have been widely used in many areas such as knowledge and content management, electronic commerce and the semanticweb.
Spinning the semanticweb is not really the place to find out about this recent work.
The idea of the semanticweb is, in short, to provide that explicit identification and the taxonomy.
This, then, is the vision of the semanticweb-or at least my version of the vision-and it is a vision that is slowly turning into a reality.
Clustering ontology-based metadata in the semanticweb.
Well, the usual answer is to give an example of the kind of thing that the semanticweb will make it possible to do, and here is such an example.
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