Abstract
Identifying the global representative parts from the multilingual pivotal ontology is important for integrating local language resources into Linked Data. We present a novel method of identifying global representative classes of DBpedia ontology based on the collective popularity, calculated by the aggregation of ranking orders from Wikipedia’s local language editions. We publish the contents of this paper on http://semanticweb.kaist.ac.kr/home/index.php/DBBO.
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Evaluation data for this work is available for download at http://semanticweb.kaist.ac.kr/home/index.php/DBBO.
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Acknowledgements
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. R0101-16-0054, WiseKB: Big data based self-evolving knowledge base and reasoning platform); the Bio & Medical Technology Development Program of the NRF funded by the Korean government, MSIP(2015M3A9A7029735).
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Kim, Ek., Choi, KS. (2017). Identifying Global Representative Classes of DBpedia Ontology Through Multilingual Analysis: A Rank Aggregation Approach. In: van Erp, M., et al. Knowledge Graphs and Language Technology. ISWC 2016. Lecture Notes in Computer Science(), vol 10579. Springer, Cham. https://doi.org/10.1007/978-3-319-68723-0_5
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DOI: https://doi.org/10.1007/978-3-319-68723-0_5
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