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Supply-demand ratio and on-demand spatial service brokers: a summary of results., , , , and . IWCTS@SIGSPATIAL, page 7-12. ACM, (2016)ULAMA: A Utilization-Aware Matching Approach for robust on-demand spatial service brokers., , , and . Future Gener. Comput. Syst., (2020)Spatiotemporal Data Mining: A Computational Perspective., , , , , , and . ISPRS Int. J. Geo Inf., 4 (4): 2306-2338 (2015)Discovering non-compliant window co-occurrence patterns., , , , , and . GeoInformatica, 21 (4): 829-866 (2017)Future connected vehicles: challenges and opportunities for spatio-temporal computing., , , , , , and . SIGSPATIAL/GIS, page 14:1-14:4. ACM, (2015)Discovering Non-compliant Window Co-Occurrence Patterns: A Summary of Results., , , , and . SSTD, volume 9239 of Lecture Notes in Computer Science, page 391-410. Springer, (2015)Spatiotemporal change footprint pattern discovery: an inter-disciplinary survey., , and . WIREs Data Mining Knowl. Discov., 4 (1): 1-23 (2014)Transdisciplinary Foundations of Geospatial Data Science., , , , , , and . ISPRS Int. J. Geo Inf., 6 (12): 395 (2017)Spatiotemporal Change Footprint Pattern Discovery., , and . Encyclopedia of GIS, Springer, (2017)Supply and Demand Aware Synthetic Data Generation for On-demand Traffic with Real-world Characteristics., , , , and . IWCTS@SIGSPATIAL, page 36-41. ACM, (2017)