Conversion of Topic map metadata to RDF metadata for knowledge retrieval on the Web

Abstract

The current Web is 'machine-readable', but not 'machine-understandable'. Therefore, new methods are required for machines to exactly understand an amount of Web information resources. A proposed solution for this issue is to use machine understandable metadata to describe information resources contained on the Web. There are two leading methods to describe metadata of Web information resources. One is Topic map, ISO/IEC JTC1's standard, and the other is RDF, WSC's standard. To implement effective semantic web (machine-understandable web), semantic web must handle all metadata of web information resources. For this, the necessity of interoperability is needed between Topic map area and RDF area. There are some previous researches on conversion method between Topic map and RDF, but these methods generate some loss of meaning or complicated result. In this paper, a new method to solve these issues is proposed. This method decreases the loss of implied semantics in comparison with the previous conversion methods and generate clear RDF graph. © Springer-Verlag Berlin Heidelberg 2005.