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Querying Fuzzy Spatiotemporal Data Using XQuery

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Modeling Fuzzy Spatiotemporal Data with XML

Part of the book series: Studies in Computational Intelligence ((SCI,volume 894))

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Abstract

How to accurately handle query criteria based on user’s preferences has become a key technology for querying fuzzy spatiotemporal data, typically collected by modern monitoring devices such as GPS receivers and sensors. However, although fuzzy logic is incorporated in querying fuzzy spatiotemporal data and querying fuzzy data in XML, relatively little work has been carried out in querying fuzzy spatiotemporal in XML. In this paper, we propose an approach for querying fuzzy spatiotemporal data using XQuery. On the basis of its architecture, we make extensions to XQuery language. The extensions consist of the new xs: truth data type intended to represent gradual truth degrees , and the new Val element and the new Poss attribute to handle satisfaction degrees . Furthermore, fuzzy spatiotemporal linguistic terms are extended to declare fuzzy terms and use them in query expressions. Additionally, FLWOR are extended to support fuzzy spatiotemporal queries. After extensions of XQuery on fuzzy spatiotemporal data, we present real case query examples, discuss crucial details of their processing, and present evaluations of each query example. Finally, the comparative study demonstrates the advantages of our approach.

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

    Zongmin Ma

  2. College of Information Science and Engineering, Northeastern University (Qinhuangdao), Qinhuangdao, Hebei, China

    Luyi Bai

  3. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

    Li Yan

Authors
  1. Zongmin Ma
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  2. Luyi Bai
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  3. Li Yan
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Correspondence to Zongmin Ma .

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Ma, Z., Bai, L., Yan, L. (2020). Querying Fuzzy Spatiotemporal Data Using XQuery. In: Modeling Fuzzy Spatiotemporal Data with XML. Studies in Computational Intelligence, vol 894. Springer, Cham. https://doi.org/10.1007/978-3-030-41999-8_7

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