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Semantic Reasoning Technology on Temporal Knowledge Graph

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Web Information Systems and Applications (WISA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13579))

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Abstract

Semantic reasoning techniques based on knowledge graphs have been widely studied since they were proposed. Previous studies are mostly based on closed-world assumptions, which cannot reason about unknown facts. To this end, we propose the Two-Stage Temporal Reasoning Model (TSTR) for reasoning about future facts. In the first stage, probability of future facts occurring is reasoned using repeated information in history. In the second stage, the semantics of the neighborhood nodes are aggregated using the structural encoder and the temporal information is captured using the temporal encoder. The predicted probabilities are obtained by the decoder. Finally, the candidate entity probabilities of the two-stage reasoning are weighted to achieve the prediction of the two-stage fusion. We tested the performance of the TSTR on public datasets and the results demonstrated the effectiveness of the TSTR.

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Authors and Affiliations

  1. National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

    Jianuo Li, Feng Zhao & Hai Jin

Authors
  1. Jianuo Li
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  2. Feng Zhao
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  3. Hai Jin
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Correspondence to Jianuo Li .

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Editors and Affiliations

  1. National University of Defense Technology, Changsha, China

    Xiang Zhao

  2. Guangzhou University, Guangzhou, China

    Shiyu Yang

  3. Tianjin University, Tianjin, China

    Xin Wang

  4. Deakin University, Melbourne, VIC, Australia

    Jianxin Li

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Li, J., Zhao, F., Jin, H. (2022). Semantic Reasoning Technology on Temporal Knowledge Graph. In: Zhao, X., Yang, S., Wang, X., Li, J. (eds) Web Information Systems and Applications. WISA 2022. Lecture Notes in Computer Science, vol 13579. Springer, Cham. https://doi.org/10.1007/978-3-031-20309-1_10

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  • DOI: https://doi.org/10.1007/978-3-031-20309-1_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20308-4

  • Online ISBN: 978-3-031-20309-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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