Fast discovery of multidimensional subsequences for robust trajectory classification
Federal University of Santa Catarina（圣卡塔琳娜联邦大学）
英文摘要：
Trajectory classification tasks became more complex as large volumes of mobility data are being generated every day and enriched with new sources of information, such as social networks and IoT sensors. Fast classification algorithms are essential for discovering knowledge in trajectory data for real applications. In this work we propose a method for fast discovery of subtrajectories with the reduction of the search space and the optimization of the MASTERMovelets method, which has proven to be effective for discovering interpretable patterns in classification problems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
