MARC: a robust method for multiple-aspect trajectory classification via space, time, and semantic embeddings
暂无分享,去创建一个
Vania Bogorny | Andrea Esuli | Chiara Renso | Camila Leite da Silva | Lucas May Petry | C. Renso | V. Bogorny | Andrea Esuli
[1] Victor S. Lempitsky,et al. Learning Deep Embeddings with Histogram Loss , 2016, NIPS.
[2] Vania Bogorny,et al. Discovering Heterogeneous Subsequences for Trajectory Classification , 2019, ArXiv.
[3] Christopher D. Manning,et al. Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..
[4] Bettina Speckmann,et al. Analysis and visualisation of movement: an interdisciplinary review , 2015, Movement Ecology.
[5] Albert-László Barabási,et al. Understanding individual human mobility patterns , 2008, Nature.
[6] Vania Bogorny,et al. A Rule-based Method for Discovering Trajectory Profiles , 2015, SEKE.
[7] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[8] Jed A. Long,et al. Weather effects on human mobility: a study using multi-channel sequence analysis , 2018, Comput. Environ. Urban Syst..
[9] K. Safi,et al. Temporal segmentation of animal trajectories informed by habitat use , 2016 .
[10] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[11] Bettina Speckmann,et al. Context-Aware Similarity of Trajectories , 2012, GIScience.
[12] Daqing Zhang,et al. Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[13] Kevin Heaslip,et al. Inferring transportation modes from GPS trajectories using a convolutional neural network , 2018, ArXiv.
[14] Tijs Neutens,et al. Extracting spatio‐temporal patterns in animal trajectories: an ecological application of sequence analysis methods , 2016 .
[15] Qiang Gao,et al. Trajectory-User Linking via Variational AutoEncoder , 2018, IJCAI.
[16] Qiang Gao,et al. Identifying Human Mobility via Trajectory Embeddings , 2017, IJCAI.
[17] Daqing Zhang,et al. Participatory Cultural Mapping Based on Collective Behavior Data in Location-Based Social Networks , 2016, ACM Trans. Intell. Syst. Technol..
[18] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[19] Piotr Jankowski,et al. Privacy and spatial pattern preservation in masked GPS trajectory data , 2016, Int. J. Geogr. Inf. Sci..
[20] Vania Bogorny,et al. Multiple aspect trajectory data analysis: research challenges and opportunities , 2016, GeoInfo.
[21] Xing Xie,et al. Understanding transportation modes based on GPS data for web applications , 2010, TWEB.
[22] Vania Bogorny,et al. MASTER: A multiple aspect view on trajectories , 2019, Trans. GIS.
[23] Vania Bogorny,et al. Multidimensional Similarity Measuring for Semantic Trajectories , 2016, Trans. GIS.
[24] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[25] Filip Biljecki,et al. Transportation mode-based segmentation and classification of movement trajectories , 2013, Int. J. Geogr. Inf. Sci..
[26] Junfeng Zhao,et al. Trip2Vec: a deep embedding approach for clustering and profiling taxi trip purposes , 2018, Personal and Ubiquitous Computing.
[27] Yang Wang,et al. Identifying Different Transportation Modes from Trajectory Data Using Tree-Based Ensemble Classifiers , 2017, ISPRS Int. J. Geo Inf..
[28] Michael J. Fischer,et al. The String-to-String Correction Problem , 1974, JACM.
[29] Robert Weibel,et al. Revealing the physics of movement: Comparing the similarity of movement characteristics of different types of moving objects , 2009, Comput. Environ. Urban Syst..
[30] Chao Zhang,et al. DeepMove: Predicting Human Mobility with Attentional Recurrent Networks , 2018, WWW.
[31] Edward Y. Chang,et al. A time-aware trajectory embedding model for next-location recommendation , 2017, Knowledge and Information Systems.
[32] Marco Heurich,et al. Individual Movement - Sequence Analysis Method (IM-SAM): characterizing spatio-temporal patterns of animal habitat use across landscapes , 2020, Int. J. Geogr. Inf. Sci..
[33] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[34] Quoc V. Le,et al. Distributed Representations of Sentences and Documents , 2014, ICML.
[35] Jure Leskovec,et al. Friendship and mobility: user movement in location-based social networks , 2011, KDD.
[36] Marco Heurich,et al. An event-based conceptual model for context-aware movement analysis , 2011, Int. J. Geogr. Inf. Sci..
[37] Jae-Gil Lee,et al. TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering , 2008, Proc. VLDB Endow..
[38] Jiawei Han,et al. The environmental-data automated track annotation (Env-DATA) system: linking animal tracks with environmental data , 2013, Movement ecology.
[39] Stan Matwin,et al. Predicting Transportation Modes of GPS Trajectories using Feature Engineering and Noise Removal , 2018, Canadian Conference on AI.
[40] Andrew W. Senior,et al. Long short-term memory recurrent neural network architectures for large scale acoustic modeling , 2014, INTERSPEECH.
[41] Dhaval Patel. Incorporating duration and region association information in trajectory classification , 2013, J. Locat. Based Serv..
[42] Shan Wang,et al. A General Multi-Context Embedding Model for Mining Human Trajectory Data , 2016, IEEE Transactions on Knowledge and Data Engineering.
[43] Vania Bogorny,et al. MOVELETS: exploring relevant subtrajectories for robust trajectory classification , 2018, SAC.
[44] Vania Bogorny,et al. Towards semantic‐aware multiple‐aspect trajectory similarity measuring , 2019, Trans. GIS.