Trip2Vec: a deep embedding approach for clustering and profiling taxi trip purposes
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Junfeng Zhao | Chao Chen | Yasha Wang | Xuefeng Xie | Chengwu Liao | Yasha Wang | Junfeng Zhao | Chengwu Liao | Junfeng Zhao | Xuefeng Xie | Chao Chen | Chao Chen
[1] J. A. Hartigan,et al. A k-means clustering algorithm , 1979 .
[2] Changsheng Li,et al. Autoencoder Regularized Network For Driving Style Representation Learning , 2017, IJCAI.
[3] Xuan Song,et al. DeepTransport: Prediction and Simulation of Human Mobility and Transportation Mode at a Citywide Level , 2016, IJCAI.
[4] Qi Han,et al. The Emergence of Visual Crowdsensing: Challenges and Opportunities , 2017, IEEE Communications Surveys & Tutorials.
[5] Chiara Renso,et al. Inferring human activities from GPS tracks , 2013, UrbComp '13.
[6] Zhongwei Deng,et al. Deriving Rules for Trip Purpose Identification from GPS Travel Survey Data and Land Use Data: A Machine Learning Approach , 2010 .
[7] Zhaohui Wu,et al. TripPlanner: Personalized Trip Planning Leveraging Heterogeneous Crowdsourced Digital Footprints , 2015, IEEE Transactions on Intelligent Transportation Systems.
[8] Xiaolei Ma,et al. Mining smart card data for transit riders’ travel patterns , 2013 .
[9] Yu Liu,et al. Inferring trip purposes and uncovering travel patterns from taxi trajectory data , 2016 .
[10] Stan Matwin,et al. TrajectoryNet: an embedded GPS trajectory representation for point-based classification using recurrent neural networks , 2017, CASCON.
[11] Zhen Zhou,et al. MA-SSR: A Memetic Algorithm for Skyline Scenic Routes Planning Leveraging Heterogeneous User-Generated Digital Footprints , 2017, IEEE Transactions on Vehicular Technology.
[12] Bo An,et al. POI2Vec: Geographical Latent Representation for Predicting Future Visitors , 2017, AAAI.
[13] Guangnian Xiao,et al. Travel Mode Detection Based on Neural Networks and Particle Swarm Optimization , 2015, Inf..
[14] Toshiyuki Yamamoto,et al. Deriving Personal Trip Data from GPS Data: A Literature Review on the Existing Methodologies , 2014 .
[15] Jiawei Han,et al. Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation , 2017, KDD.
[16] Bruno Agard,et al. Measuring transit use variability with smart-card data , 2007 .
[17] Zhu Wang,et al. Wi-Fi CSI-Based Behavior Recognition: From Signals and Actions to Activities , 2017, IEEE Communications Magazine.
[18] Lin Sun,et al. Understanding Taxi Service Strategies From Taxi GPS Traces , 2015, IEEE Transactions on Intelligent Transportation Systems.
[19] Daqing Zhang,et al. From taxi GPS traces to social and community dynamics , 2013, ACM Comput. Surv..
[20] Doug Beeferman,et al. Agglomerative clustering of a search engine query log , 2000, KDD '00.
[21] Henriette Cramer,et al. Performing a check-in: emerging practices, norms and 'conflicts' in location-sharing using foursquare , 2011, Mobile HCI.
[22] John Krumm,et al. Placer: semantic place labels from diary data , 2013, UbiComp.
[23] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[24] Zhi-Hua Zhou,et al. B-Planner: Planning Bidirectional Night Bus Routes Using Large-Scale Taxi GPS Traces , 2014, IEEE Transactions on Intelligent Transportation Systems.
[25] Daqing Zhang,et al. Sparse mobile crowdsensing: challenges and opportunities , 2016, IEEE Communications Magazine.
[26] Pascal Vincent,et al. Artificial Neural Networks Applied to Taxi Destination Prediction , 2015, DC@PKDD/ECML.
[27] Victor C. S. Lee,et al. TaxiRec: Recommending Road Clusters to Taxi Drivers Using Ranking-Based Extreme Learning Machines , 2018, IEEE Trans. Knowl. Data Eng..
[28] Zhu Wang,et al. The Road to the Chinese Smart City: Progress, Challenges, and Future Directions , 2016, IT Professional.
[29] Yu Zheng,et al. Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction , 2016, AAAI.
[30] Jie Bao,et al. Exploring Bikesharing Travel Patterns and Trip Purposes Using Smart Card Data and Online Point of Interests , 2017 .
[31] Elsevier Sdol,et al. Transportation Research Part C: Emerging Technologies , 2009 .
[32] D. Ruths,et al. Social media for large studies of behavior , 2014, Science.
[33] Zhu Wang,et al. ScenicPlanner: planning scenic travel routes leveraging heterogeneous user-generated digital footprints , 2017, Frontiers of Computer Science.
[34] Silvio Savarese,et al. Social LSTM: Human Trajectory Prediction in Crowded Spaces , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Pengfei Wang,et al. Human Mobility Synchronization and Trip Purpose Detection with Mixture of Hawkes Processes , 2017, KDD.
[36] Victor C. S. Lee,et al. TaxiRec: Recommending Road Clusters to Taxi Drivers Using Ranking-Based Extreme Learning Machines , 2015, IEEE Transactions on Knowledge and Data Engineering.
[37] Yuki Endo,et al. Deep Feature Extraction from Trajectories for Transportation Mode Estimation , 2016, PAKDD.
[38] Feng Xia,et al. Mobility Dataset Generation for Vehicular Social Networks Based on Floating Car Data , 2018, IEEE Transactions on Vehicular Technology.
[39] Huachun Tan,et al. Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework , 2016, ArXiv.
[40] Jean Louise Wolf,et al. Using GPS data loggers to replace travel diaries in the collection of travel data , 2000 .
[41] Qi Han,et al. Worker-Contributed Data Utility Measurement for Visual Crowdsensing Systems , 2017, IEEE Transactions on Mobile Computing.
[42] Daqing Zhang,et al. crowddeliver: Planning City-Wide Package Delivery Paths Leveraging the Crowd of Taxis , 2017, IEEE Transactions on Intelligent Transportation Systems.
[43] Chao Chen,et al. TripImputor: Real-Time Imputing Taxi Trip Purpose Leveraging Multi-Sourced Urban Data , 2018, IEEE Transactions on Intelligent Transportation Systems.
[44] Tian Lan,et al. Zooming into individuals to understand the collective: A review of trajectory-based travel behaviour studies , 2014 .
[45] Gerhard Tröster,et al. Inferring travel purpose from crowd-augmented human mobility data , 2014, Urb-IoT.
[46] Kees Maat,et al. Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands , 2009 .
[47] Daqing Zhang,et al. Fine-Grained Urban Event Detection and Characterization Based on Tensor Cofactorization , 2017, IEEE Transactions on Human-Machine Systems.
[48] Bin Guo,et al. Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints , 2016, IEEE Transactions on Human-Machine Systems.
[49] Rui Jiang,et al. Inferring the Travel Purposes of Passenger Groups for Better Understanding of Passengers , 2015, IEEE Transactions on Intelligent Transportation Systems.
[50] Jiujun Cheng,et al. PRACE: A Taxi Recommender for Finding Passengers with Deep Learning Approaches , 2017, ICIC.
[51] Junjie Wu,et al. Traffic Speed Prediction and Congestion Source Exploration: A Deep Learning Method , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).