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SDPedia: from DBpedia to domain-micropedia

SDPedia: from DBpedia to domain-micropedia PurposeOnline encyclopedia has facilitated users to easily access interesting knowledge and find solutions for daily problems. However, for the staff in specific domains, especially in secret-related domains, a domain-micropedia is still necessary for work.Design/methodology/approachIn this paper, the authors propose an approach to extract entities from DBpedia and construct the SDPedia in space debris mitigation domain. First, the authors select the root categories about space debris mitigation domain by manual methods. Subsequently, the authors propose Distance of Electrical Resistance, Pages Common Words and AVDP algorithms to implement the extraction. The authors also achieve the data visualization by generating swf files and embedding them into web pages.FindingsIn the experiments, the precision, recall and F1-measure are used to evaluate the proposed algorithms. The authors set a series of thresholds to pursue the highest F1-measure. The experimental data indicate that the AVDP algorithm gets the highest F1-measure and is statistically effective for the entities extraction from DBpedia.Originality/valueThe authors propose an approach of deriving linked data from DBpedia and construct their own SDPedia, which has been applied in the space debris mitigation domain currently. Compared with DBpedia, the authors also add the linked data visualization. Moreover, the methodology can be used in many other domains in the future. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Web Information Systems Emerald Publishing

SDPedia: from DBpedia to domain-micropedia

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1744-0084
DOI
10.1108/IJWIS-05-2017-0040
Publisher site
See Article on Publisher Site

Abstract

PurposeOnline encyclopedia has facilitated users to easily access interesting knowledge and find solutions for daily problems. However, for the staff in specific domains, especially in secret-related domains, a domain-micropedia is still necessary for work.Design/methodology/approachIn this paper, the authors propose an approach to extract entities from DBpedia and construct the SDPedia in space debris mitigation domain. First, the authors select the root categories about space debris mitigation domain by manual methods. Subsequently, the authors propose Distance of Electrical Resistance, Pages Common Words and AVDP algorithms to implement the extraction. The authors also achieve the data visualization by generating swf files and embedding them into web pages.FindingsIn the experiments, the precision, recall and F1-measure are used to evaluate the proposed algorithms. The authors set a series of thresholds to pursue the highest F1-measure. The experimental data indicate that the AVDP algorithm gets the highest F1-measure and is statistically effective for the entities extraction from DBpedia.Originality/valueThe authors propose an approach of deriving linked data from DBpedia and construct their own SDPedia, which has been applied in the space debris mitigation domain currently. Compared with DBpedia, the authors also add the linked data visualization. Moreover, the methodology can be used in many other domains in the future.

Journal

International Journal of Web Information SystemsEmerald Publishing

Published: Jun 18, 2018

References