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Path-based approximate matching of fuzzy spatiotemporal RDF data

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Abstract

As fuzzy spatiotemporal information continuously increases in RDF database, it is challenging to model and query fuzzy spatiotemporal RDF data efficiently and effectively. However, various researches are studied in temporal RDF database, spatial RDF database, and spatiotemporal RDF database. Querying fuzzy spatiotemporal RDF data has received relatively little attention, especially approximate matching of fuzzy spatiotemporal RDF data. To accomplish this, we first study fuzzy spatiotemporal RDF data graph, spatiotemporal RDF query graph, and path of fuzzy spatiotemporal RDF data graph. Then, we propose a scoring function for approximate evaluation of fuzzy spatiotemporal RDF data graph and spatiotemporal RDF query graph. After dividing the fuzzy spatiotemporal RDF data graphs into five categories based on their structure, we propose the decomposition algorithm, matching algorithm, and combination algorithm for approximate matching of fuzzy spatiotemporal RDF data. Our approach adopts path-based matching so that it is easy to discover the relations between two vertices in fuzzy spatiotemporal RDF data graph. Finally, the experimental results demonstrate the performance advantages of our approach.

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Acknowledgements

The authors would like to express their gratitude to the anonymous reviewers for providing very helpful suggestions.

Funding

The work was supported by the National Natural Science Foundation of China (61402087), the Natural Science Foundation of Hebei Province (F2022501015), and the Fundamental Research Funds for the Central Universities (2023GFYD003).

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Authors and Affiliations

  1. School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao, 066004, China

    Lin Zhu, Jiajia Lu & Luyi Bai

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  1. Lin Zhu
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  2. Jiajia Lu
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Contributions

Lin Zhu: Methodology, Formal analysis, Writing - original draft, Writing - review & editing; Jiajia Lu: Investigation, Validation, Formal analysis, Writing - original draft; Luyi Bai: Conceptualization, Methodology, Formal analysis, Funding acquisition, Writing - original draft, Writing - review & editing.

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Correspondence to Luyi Bai.

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Zhu, L., Lu, J. & Bai, L. Path-based approximate matching of fuzzy spatiotemporal RDF data. World Wide Web 27, 11 (2024). https://doi.org/10.1007/s11280-024-01247-6

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