The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Propomos um método aprimorado para traduzir mapas de tópicos para esquema RDF/RDF, para realizar a Web Semântica. Uma questão crítica para a Web Semântica é descrever com eficiência e precisão os recursos de informação da Web, ou seja, os metadados da Web. Dois padrões representativos, Topic Maps e RDF, foram usados para metadados da Web. A padronização baseada em RDF e a implementação da Web Semântica têm sido ativamente realizadas. Como a Web Semântica deve aceitar e compreender todos os recursos de informação da Web representados por outros métodos, a tradução de mapas de tópicos para RDF tornou-se um problema. Embora muitos métodos de tradução de mapas de tópicos para RDF tenham sido desenvolvidos, eles ainda apresentam vários problemas (por exemplo, perda semântica, expressão complexa, etc.). Nosso método de tradução fornece uma solução aprimorada para esses problemas. Este método apresenta menor perda semântica do que os métodos anteriores devido à extração tanto da semântica explícita quanto da semântica implícita. Comparado aos métodos anteriores, nosso método reduz a complexidade de codificação do RDF resultante. Além disso, em termos de reversibilidade, o método proposto regenera todas as construções dos Mapas Tópicos em uma fonte original quando é traduzido reversamente.
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Shinae SHIN, Dongwon JEONG, Doo-Kwon BAIK, "Novel Topic Maps to RDF/RDF Schema Translation Method" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 11, pp. 2626-2637, November 2008, doi: 10.1093/ietisy/e91-d.11.2626.
Abstract: We propose an enhanced method for translating Topic Maps to RDF/RDF Schema, to realize the Semantic Web. A critical issue for the Semantic Web is to efficiently and precisely describe Web information resources, i.e., Web metadata. Two representative standards, Topic Maps and RDF have been used for Web metadata. RDF-based standardization and implementation of the Semantic Web have been actively performed. Since the Semantic Web must accept and understand all Web information resources that are represented with the other methods, Topic Maps-to-RDF translation has become an issue. Even though many Topic Maps to RDF translation methods have been devised, they still have several problems (e.g. semantic loss, complex expression, etc.). Our translation method provides an improved solution to these problems. This method shows lower semantic loss than the previous methods due to extract both explicit semantics and implicit semantics. Compared to the previous methods, our method reduces the encoding complexity of resulting RDF. In addition, in terms of reversibility, the proposed method regenerates all Topic Maps constructs in an original source when is reverse translated.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.11.2626/_p
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@ARTICLE{e91-d_11_2626,
author={Shinae SHIN, Dongwon JEONG, Doo-Kwon BAIK, },
journal={IEICE TRANSACTIONS on Information},
title={Novel Topic Maps to RDF/RDF Schema Translation Method},
year={2008},
volume={E91-D},
number={11},
pages={2626-2637},
abstract={We propose an enhanced method for translating Topic Maps to RDF/RDF Schema, to realize the Semantic Web. A critical issue for the Semantic Web is to efficiently and precisely describe Web information resources, i.e., Web metadata. Two representative standards, Topic Maps and RDF have been used for Web metadata. RDF-based standardization and implementation of the Semantic Web have been actively performed. Since the Semantic Web must accept and understand all Web information resources that are represented with the other methods, Topic Maps-to-RDF translation has become an issue. Even though many Topic Maps to RDF translation methods have been devised, they still have several problems (e.g. semantic loss, complex expression, etc.). Our translation method provides an improved solution to these problems. This method shows lower semantic loss than the previous methods due to extract both explicit semantics and implicit semantics. Compared to the previous methods, our method reduces the encoding complexity of resulting RDF. In addition, in terms of reversibility, the proposed method regenerates all Topic Maps constructs in an original source when is reverse translated.},
keywords={},
doi={10.1093/ietisy/e91-d.11.2626},
ISSN={1745-1361},
month={November},}
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TY - JOUR
TI - Novel Topic Maps to RDF/RDF Schema Translation Method
T2 - IEICE TRANSACTIONS on Information
SP - 2626
EP - 2637
AU - Shinae SHIN
AU - Dongwon JEONG
AU - Doo-Kwon BAIK
PY - 2008
DO - 10.1093/ietisy/e91-d.11.2626
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2008
AB - We propose an enhanced method for translating Topic Maps to RDF/RDF Schema, to realize the Semantic Web. A critical issue for the Semantic Web is to efficiently and precisely describe Web information resources, i.e., Web metadata. Two representative standards, Topic Maps and RDF have been used for Web metadata. RDF-based standardization and implementation of the Semantic Web have been actively performed. Since the Semantic Web must accept and understand all Web information resources that are represented with the other methods, Topic Maps-to-RDF translation has become an issue. Even though many Topic Maps to RDF translation methods have been devised, they still have several problems (e.g. semantic loss, complex expression, etc.). Our translation method provides an improved solution to these problems. This method shows lower semantic loss than the previous methods due to extract both explicit semantics and implicit semantics. Compared to the previous methods, our method reduces the encoding complexity of resulting RDF. In addition, in terms of reversibility, the proposed method regenerates all Topic Maps constructs in an original source when is reverse translated.
ER -