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TGKG: New Data Graph Based on Game Ontology

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1466))

Abstract

With the advent of the big data era, knowledge graph embodies great advantages. Especially in game domain, building a knowledge graph is of great value. However, some open-domain knowledge bases is not designed for games and the amount of game data is relatively limited. In this paper, we propose a game ontology. In addition, in the process of constructing game knowledge graph, we found it is import to identify an entity is a game entity or not. Thus, we propose a new DLC entity identification model to help us use the ontology to build the graph.

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Notes

  1. 1.

    http://www.semanticweb.org/databrain/ontologies/tgkgdata/.

  2. 2.

    https://www.w3.org/TR/owl2-overview/.

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Correspondence to Wenqiang Liu .

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Sang, J., Liu, W., Wu, B., Guo, H., Huang, D., Jiang, Y. (2021). TGKG: New Data Graph Based on Game Ontology. In: Qin, B., Jin, Z., Wang, H., Pan, J., Liu, Y., An, B. (eds) Knowledge Graph and Semantic Computing: Knowledge Graph Empowers New Infrastructure Construction. CCKS 2021. Communications in Computer and Information Science, vol 1466. Springer, Singapore. https://doi.org/10.1007/978-981-16-6471-7_20

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  • DOI: https://doi.org/10.1007/978-981-16-6471-7_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-6470-0

  • Online ISBN: 978-981-16-6471-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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