图7. 驻留点检测类SQL语句 在一些研究[1-3][6-7]中,为了保证检测结果(加油事件、停车等客事件、妥投事件)的质量,基于监督学习的模型可以被进一步使用在检测得到的驻留点上。通过提取驻留点中的一些特征,可以过滤得到只属于某一类特定事件的驻留点,让后续分析变得更为准确。 三、 总结以上就是本次驻留点应用及经典算法的分享。通过本文,我们了解了驻留点的一些重要应用。通过其与路网、POI、卫星图像等的关联分析,我们可以发现很多有趣的知识。未来,JUST将集成更多关联筛选的功能,快速从数据中得到洞察。参考文献:[1] Zhang, Fuzheng, et al. "Sensing the pulse of urban refueling behavior." Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. 2013.[2] Zhang, Fuzheng, et al. "Sensing the pulse of urban refueling behavior: A perspective from taxi mobility." ACM Transactions on Intelligent Systems and Technology (TIST) 6.3 (2015): 1-23.[3] Ruan, Sijie, et al. "Doing in One Go: Delivery Time Inference Based on Couriers' Trajectories." Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2020.[4] Zheng, Yu, et al. "Mining interesting locations and travel sequences from GPS trajectories." Proceedings of the 18th international conference on World wide web. 2009.[5] Zheng, Yu, and Xing Xie. "Learning travel recommendations from user-generated GPS traces." ACM Transactions on Intelligent Systems and Technology (TIST) 2.1 (2011): 1-29.[6] Yuan, Jing, et al. "Where to find my next passenger." Proceedings of the 13th international conference on Ubiquitous computing. 2011.[7] Yuan, Jing, et al. "T-finder: A recommender system for finding passengers and vacant taxis." IEEE Transactions on knowledge and data engineering 25.10 (2012): 2390-2403.[8] “京东城市”微信公众号. “一屏联动64个部门,京东城市助力南通建成全国首个市域治理现代化指挥中心”, 2020.[9] 麻志鹏,等. “查找仓库的方法和装置” 中国专利(已授权), 2019.[10] Ye, Yang, et al. "Mining individual life pattern based on location history." 2009 tenth international conference on mobile data management: Systems, services and middleware. IEEE, 2009.[11] Zheng, Yu. "Trajectory data mining: an overview." ACM Transactions on Intelligent Systems and Technology (TIST) 6.3 (2015): 1-41.[12] https://just.urban-computing.cn/
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