Searching for the Knowledge in the Semantic Web

This paper discusses the prerequisites for design, and presents an approach for representing rules in the machine understandable form, which is based on the current efforts in achieving themachine understandable semantic of information.

Abstract

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