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• W3213266875 abstract "The rapid development of positioning technology produces an extremely large volume of spatio-temporal data with various geometry types such as point, line string, polygon, or a mixed combination of them. As one of the most basic but time-consuming operations, k nearest neighbors join (kNN join) has attracted much attention. However, most existing works for kNN join either ignore temporal information or consider point data only." @default.
• W3213266875 created "2021-11-22" @default.
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• W3213266875 date "2021-11-02" @default.
• W3213266875 modified "2023-10-17" @default.
• W3213266875 title "Distributed Spatio-Temporal k Nearest Neighbors Join" @default.
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• W3213266875 doi "https://doi.org/10.1145/3474717.3484209" @default.
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