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• W2766779636 abstract "Spatiotemporal co-occurrences are the appearances of spatial and temporal overlap relationships among trajectory-based spatiotemporal instances with region-based geometric representations. Assessing the significance of spatiotemporal co-occurrences plays an important role in the spatiotemporal frequent pattern mining applications of moving region objects. A spatiotemporal version of the popular Jaccard measure has been used for measuring the strength of spatiotemporal co-occurrences. We will demonstrate the shortcomings of the Jaccard ( J ) measure when it is used for assessing the significance of co-occurrences among spatiotemporal instances with highly different spatiotemporal evolution characteristics. We will present two extended novel measures ( J + and J * ) that address the problems linked to the J measure. Our work includes algorithms for the significance measure calculations, the proofs and explanations about the key properties of measures, and a detailed experimental evaluation section. Our experiments include in-depth relevancy and running time analyses demonstrating the suitability of our proposed measures for spatiotemporal frequent pattern mining algorithms." @default.
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• W2766779636 date "2017-09-30" @default.
• W2766779636 modified "2023-10-10" @default.
• W2766779636 title "Measuring the Significance of Spatiotemporal Co-Occurrences" @default.
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• W2766779636 doi "https://doi.org/10.1145/3139351" @default.
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