A Multi-Task Sequential State Model for the Human Trajectory Data Understanding

Big Data Research - Tập 25 - Trang 100220 - 2021
Jiabi Zheng1, Zhenguo Yang1, Wenyin Liu1,2
1School of Computer Science and Technology,Guangdong University of Technology, Guangzhou 510006, China
2Cyberspace Security Research Center, Peng Cheng Laboratory, Shenzhen, 518066, China

Tài liệu tham khảo

Zheng, 2015, Trajectory data mining: an overview, ACM Trans. Intell. Syst. Technol., 6, 1, 10.1145/2743025 Lee, 2015, Geospatial big data: challenges and opportunities, Big Data Res., 2, 74, 10.1016/j.bdr.2015.01.003 Parent, 2013, Semantic trajectories modeling and analysis, ACM Comput. Surv., 45, 1, 10.1145/2501654.2501656 Lee, 2007, Trajectory clustering: a partition-and-group framework, 593 Wang, 2019, Fast large-scale trajectory clustering, Proc. VLDB Endow., 13, 29, 10.14778/3357377.3357380 Eagle, 2009, Eigenbehaviors: identifying structure in routine, Behav. Ecol. Sociobiol., 63, 1057, 10.1007/s00265-009-0739-0 Gonzalez, 2008, Understanding individual human mobility patterns, Nature, 453, 779, 10.1038/nature06958 Li, 2019, Next and next new poi recommendation via latent behavior pattern inference, ACM Trans. Inf. Syst., 37, 1, 10.1145/3354187 Cao, 2019, Habit2vec: trajectory semantic embedding for living pattern recognition in population, IEEE Trans. Mob. Comput., 19, 1096, 10.1109/TMC.2019.2902403 Han, 2020, Contextualized point-of-interest recommendation, 2484 Takeuchi, 2006, Cityvoyager: an outdoor recommendation system based on user location history, 625 Ye, 2009, Mining individual life pattern based on location history, 1 Jeung, 2008, A hybrid prediction model for moving objects, 70 Shang, 2014, Inferring gas consumption and pollution emission of vehicles throughout a city, 1027 Zheng, 2011, Learning travel recommendations from user-generated gps traces, ACM Trans. Intell. Syst. Technol., 2, 1, 10.1145/1889681.1889683 Gao, 2017, Identifying human mobility via trajectory embeddings, 1689 Patterson, 2003, Inferring high-level behavior from low-level sensors, 73 Liao, 2007, Learning and inferring transportation routines, Artif. Intell., 171, 311, 10.1016/j.artint.2007.01.006 Ying, 2010, Mining user similarity from semantic trajectories, 19 Liu, 2015, Points of interest recommendation from gps trajectories, Int. J. Geogr. Inf. Sci., 29, 953, 10.1080/13658816.2015.1005094 Yan, 2013, Semantic trajectories: mobility data computation and annotation, ACM Trans. Intell. Syst. Technol., 4, 1, 10.1145/2483669.2483682 Etemad, 2020, Sws: an unsupervised trajectory segmentation algorithm based on change detection with interpolation kernels, GeoInformatica, 1 Lv, 2016, The discovery of personally semantic places based on trajectory data mining, Neurocomputing, 173, 1142, 10.1016/j.neucom.2015.08.071 Qiu, 2020, Residence and workplace recovery: user privacy risk in mobility data, 15 Cao, 2010, Mining significant semantic locations from gps data, Proc. VLDB Endow., 3, 1009, 10.14778/1920841.1920968 Zhang, 2020, Efficient mining of hotspot regional patterns with multi-semantic trajectories, Big Data Res., 22, 10.1016/j.bdr.2020.100157 Bermingham, 2019, Mining place-matching patterns from spatio-temporal trajectories using complex real-world places, Expert Syst. Appl., 122, 334, 10.1016/j.eswa.2019.01.027 Li, 2019, Multi-task recurrent neural networks and higher-order Markov random fields for stock price movement prediction: multi-task rnn and higher-order mrfs for stock price classification, 1141