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A Situation Knowledge Graph Construction Mechanism with Context-Aware Services for Smart Cockpit

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Web and Big Data (APWeb-WAIM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14332))

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Abstract

With the continuous development of intelligence and network connectivity, the smart cockpit gradually transforms into a multifunctional value space. Smart devices are heterogeneous, massive, complex, and contextually dynamic, which makes the services provided by the system inaccurate. Introducing knowledge graphs in smart cockpit situations can meet users’ needs in specific scenarios while delivering experiences that exceed expectations. This paper constructs a smart cockpit situation model with context, service, and user as the core elements, not only refining the context dimension but also incorporating context into the definition of service. Firstly, we analyze the elements that constitute the smart cockpit situation model and explore the connection between them. Secondly, a top-down approach is used to construct the smart cockpit situation ontology using the smart cockpit situation model as a guide. Finally, the smart cockpit situation model is instantiated to build a knowledge graph for fitness scenarios. The research results show that the coverage relationships between scenarios are inferred based on the coverage relationships between contexts. Furthermore, we verify the context can improve the accuracy of the service with a family travel scenario example. The situation knowledge graph constructed in this paper cannot only comprehensively describe the smart cockpit scene data, but also the service can adapt to the dynamic changes of contextual data.

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Acknowledgements

This work was funded by the National Natural Science Foundation of China grant number U1836118, Key Laboratory of Rich Media Digital Publishing, Content Organization and Knowledge Service grant number ZD2022-10/05, and National key research and development program grant number 2020AAA0108500.

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Authors and Affiliations

  1. College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430065, China

    Xinyi Sheng, Jinguang Gu & Xiaoyu Yang

  2. Institute of Big Data Science and Engineering, Wuhan University of Science and Technology, Wuhan, 430065, China

    Jinguang Gu

  3. Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content, National Press and Publication Administration, Beijing, 100038, China

    Jinguang Gu

Authors
  1. Xinyi Sheng
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  2. Jinguang Gu
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  3. Xiaoyu Yang
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Corresponding author

Correspondence to Jinguang Gu .

Editor information

Editors and Affiliations

  1. Peng Cheng Laboratory, Shenzhen, China

    Xiangyu Song

  2. China University of Geosciences, Wuhan, China

    Ruyi Feng

  3. China University of Geosciences, Wuhan, China

    Yunliang Chen

  4. Deakin University, Burwood, VIC, Australia

    Jianxin Li

  5. University of Exeter, Exeter, UK

    Geyong Min

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Sheng, X., Gu, J., Yang, X. (2024). A Situation Knowledge Graph Construction Mechanism with Context-Aware Services for Smart Cockpit. In: Song, X., Feng, R., Chen, Y., Li, J., Min, G. (eds) Web and Big Data. APWeb-WAIM 2023. Lecture Notes in Computer Science, vol 14332. Springer, Singapore. https://doi.org/10.1007/978-981-97-2390-4_21

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  • DOI: https://doi.org/10.1007/978-981-97-2390-4_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2389-8

  • Online ISBN: 978-981-97-2390-4

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