SDPedia: from DBpedia to domain-micropedia

Abstract

Purpose Online 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/approach In 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. Findings In 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/value The 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.