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MasterMovelets: discovering heterogeneous movelets for multiple aspect trajectory classification.

, , , , , and . Data Min. Knowl. Discov., 34 (3): 652-680 (2020)

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Examining the impact of cross-domain learning on crime prediction., , , and . J. Big Data, 8 (1): 96 (2021)Analyzing the Impact of Foursquare and Streetlight Data with Human Demographics on Future Crime Prediction., , , and . CoRR, (2020)Challenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning., , , , and . Canadian AI, volume 12109 of Lecture Notes in Computer Science, page 401-407. Springer, (2020)MasterMovelets: discovering heterogeneous movelets for multiple aspect trajectory classification., , , , , and . Data Min. Knowl. Discov., 34 (3): 652-680 (2020)Towards semantic-aware multiple-aspect trajectory similarity measuring., , , , and . Trans. GIS, 23 (5): 960-975 (2019)Discovering Heterogeneous Subsequences for Trajectory Classification., , , , and . CoRR, (2019)Traj2User: exploiting embeddings for computing similarity of users mobile behavior., , , and . CoRR, (2018)MARC: a robust method for multiple-aspect trajectory classification via space, time, and semantic embeddings., , , , and . Int. J. Geogr. Inf. Sci., 34 (7): 1428-1450 (2020)A Survey and Comparison of Trajectory Classification Methods., , and . BRACIS, page 788-793. IEEE, (2019)Exploring frequency-based approaches for efficient trajectory classification., , , , and . SAC, page 624-631. ACM, (2020)