Abstract
With the emerge of knowledge graphs in different scales like DBpedia, YAGO, and WikiData, they have become the cornerstone to support many artificial intelligence tasks. However, it is difficult for end-users to query and understand those knowledge graphs consisting of hundreds of millions of nodes and edges. To help end-users better retrieve information from RDF data and explore the knowledge graph without SPARQL or knowing the relation types, we developed an interactive visual query tool, called KG3D, which can realize connection query and pattern matching. Our tool can view the knowledge graph in 3-dimensional space and automatically convert the query to the SPARQL statement. In this paper, we present the superiority of KG3D over other tools, discuss the design motivation, and demonstrate various use cases.
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GitHub repository: https://github.com/selenesoft/kg3d.
References
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Xu, D., Wang, L., Wang, X., Li, D., Duan, J., Jia, Y. (2019). KG3D: An Interactive 3D Visualization Tool for Knowledge Graphs. In: Li, J., Wang, S., Qin, S., Li, X., Wang, S. (eds) Advanced Data Mining and Applications. ADMA 2019. Lecture Notes in Computer Science(), vol 11888. Springer, Cham. https://doi.org/10.1007/978-3-030-35231-8_67
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DOI: https://doi.org/10.1007/978-3-030-35231-8_67
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