Searching for the Knowledge in the Semantic Web

May 2002

Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2002)

Volume

Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2002)

All Papers

The machine understandable semantic of information, achieved by using an RDF(S) structure and common-shared vocabularies (ontologies) is the big step in enabling the machine-agent interoperability on the Web. Machine agents can crawl annotated web pages, search for useful information from various sources, use the information to solve tasks at hand by using the internal reasoning mechanism and background knowledge. In order to enhance their inference capabilities, machine- (and also human-) agents need to update their knowledge, using relevant knowledge sources as much as possible. One of the possible scenarios is to search for relevant knowledge on the (Semantic) Web. In this paper we discuss the prerequisites for design, and present an approach for representing rules in the machine understandable form, which is based on the current efforts in achieving the machine understandable semantic of information. Such representation of rules can serve as the backbone for a web-enabled knowledge management process. In the presented usage scenario we focus on the knowledge sharing phase in that process, i.e. on the searching for relevant knowledge (rules) on the Web.