TY - GEN
T1 - Conversion of Topic map metadata to RDF metadata for knowledge retrieval on the Web
AU - Shin, Shinae
AU - Jeong, Dongwon
AU - Baik, Doo Kwon
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
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M3 - Conference contribution
AN - SCOPUS:33745171080
SN - 3540321330
SN - 9783540321330
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 123
EP - 137
BT - Software Engineering Research and Applications - Second International Conference, SERA 2004, Revised Selected Papers
T2 - 2nd International Conference on Software Engineering Research and Applications, SERA 2004
Y2 - 5 May 2004 through 7 May 2004
ER -