Abstract
Large knowledge graphs (KGs), which are part of Linked Open Data (LOD) serve as the primary source for retrieving structured data in many Semantic Web applications. In order for machines to efficiently process the data for different data mining, entity linking and information retrieval tasks, it is always beneficial to have as many reliable facts from KGs as possible. But none of the KGs is complete on its own with respect to the number of relations describing an entity. Moreover, large KGs like DBpedia, YAGO and Wikidata appear similar in nature, but do not fully merge in terms relations of the entities from different domains. The complementary nature of different KGs can be utilized to expand the coverage of relations of the an entity. In order to achieve this, a framework for integration of entity information from different KGs using LOD, semantic similarity approaches and RDF reification is proposed in this paper.
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Acknowledgements
This work is partially funded by Fundamental Research Grant Scheme (FRGS) by Malaysia Ministry of Higher Education (Ref: FRGS/2/2013/ICT07/MMU/02/2).
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Govindapillai, S., Soon, LK., Haw, SC. (2020). LODeDeC: A Framework for Integration of Entity Relations from Knowledge Graphs. In: Wang, F., et al. Information Retrieval Technology. AIRS 2019. Lecture Notes in Computer Science(), vol 12004. Springer, Cham. https://doi.org/10.1007/978-3-030-42835-8_17
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DOI: https://doi.org/10.1007/978-3-030-42835-8_17
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