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Daily activity data that records individuals' various types of activities in daily life are widely used in many applications such as activity scheduling, activity recommendation, and policymaking.
A theory of human motivation
Abraham Harold Maslow. 1943 · 1943
Earlier work this paper cites.
A Markov chain model of human needs: An extension of Maslow’s need theory
Kae H Chung. 1969 · 1969
Earlier work this paper cites.
A test of the need hierarchy concept by a Markov model of change in need strength
John Rauschenberger, Neal Schmitt, and John E Hunter. 1980 · 1980
Earlier work this paper cites.
Toward a dynamic model of individual activity pattern formulation
WW Recker and GS Root. 1981 · 1981
Earlier work this paper cites.
Assessing self-maintenance: activities of daily living, mobility, and instrumental activities of daily living
Sidney Katz. 1983 · 1983
Earlier work this paper cites.
An introduction to hidden Markov models
Lawrence Rabiner and Biinghwang Juang. 1986 · 1986
Earlier work this paper cites.
Divergence measures based on the Shannon entropy
Jianhua Lin. 1991 · 1991
Earlier work this paper cites.
Simulation model of activity scheduling behavior
Dick Ettema, Aloys Borgers, and Harry Timmermans. 1993 · 1993
Earlier work this paper cites.
The sequenced activity mobility simulator (SAMS): an integrated approach to modeling transportation, land use and air quality
Ryuichi Kitamura, Eric I Pas, Clarisse V Lula, T Keith Lawton, and Paul E Benson. 1996 · 1996
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Introduction to reinforcement learning . Vol. 135
Richard S Sutton, Andrew G Barto, et al · 1998
Earlier work this paper cites.
ALBATROSS: multiagent, rule-based model of activity pattern decisions
Theo Arentze, Frank Hofman, Henk van Mourik, and Harry Timmermans. 2000 · 2000
Earlier work this paper cites.
Activity-based disaggregate travel demand model system with activity schedules
John L Bowman and Moshe E Ben-Akiva. 2001 · 2001
Earlier work this paper cites.
Tutorial on agent-based modeling and simulation. In WSC . IEEE, 14–pp
Charles M Macal and Michael J North. 2005 · 2005
Earlier work this paper cites.
Mining sensor data in smart environment for temporal activity prediction
Vikramaditya Jakkula and Diane J Cook. 2007 · 2007
Earlier work this paper cites.
A synthesized model of Markov chain and ERG theory for behavior forecast in collaborative prototyping
Wei-Lun Chang and Soe-Tsyr Yuan. 2008 · 2008
Earlier work this paper cites.
Multiscale agent-based consumer market modeling
Michael J North, Charles M Macal, James St Aubin, Prakash Thimmapuram, Mark Bragen, June Hahn, James Karr, Nancy Brigham, Mark E Lacy, and Delaine Hampton. 2010 · 2010
Earlier work this paper cites.
Toward a ubiquitous personalized daily-life activity recommendation service with contextual information: a services science perspective
Chen-Ya Wang, Yueh-Hsun Wu, and Seng-Cho T Chou. 2010 · 2010
Cited alongside, same era.
Markov models of molecular kinetics: Generation and validation
Jan-Hendrik Prinz, Hao Wu, Marco Sarich, Bettina Keller, Martin Senne, Martin Held, John D Chodera, Christof Schütte, and Frank Noé. 2011 · 2011
Cited alongside, same era.
Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model
Joshua Auld and Abolfazl Kouros Mohammadian. 2012 · 2012
Cited alongside, same era.
Semi-Markov processes and reliability
Nikolaos Limnios and Gheorghe Oprisan. 2012 · 2012
Cited alongside, same era.
Generating sequences with recurrent neural networks
Alex Graves. 2013 · 2013
Cited alongside, same era.
A Non-Parametric Generative Model for Human Trajectories.. In IJCAI . 3812–3817
Kun Ouyang, Reza Shokri, David S Rosenblum, and Wenzhuo Yang. 2018 · 2018
Later among the works it cites.
Neural jump stochastic differential equations
Junteng Jia and Austin R Benson. 2019 · 2019
Later among the works it cites.
Location-based social simulation. In SSTD . 218–221
Hamdi Kavak, Joon-Seok Kim, Andrew Crooks, Dieter Pfoser, Carola Wenk, and Andreas Züfle. 2019 · 2019
Later among the works it cites.
Simulating urban patterns of life: A geo-social data generation framework. In SIGSPATIAL . 576–579
Joon-Seok Kim, Hamdi Kavak, Umar Manzoor, Andrew Crooks, Dieter Pfoser, Carola Wenk, and Andreas Züfle. 2019 · 2019
Later among the works it cites.
An introduction to variational autoencoders
Diederik P Kingma, Max Welling, et al · 2019
Later among the works it cites.
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What’s your next move: User activity prediction in location-based social networks. In Proceedings of the 2013 SIAM International Conference on Data Mining . SIAM, 171–179
Jihang Ye, Zhe Zhu, and Hong Cheng. 2013 · 2013
Cited alongside, same era.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Annotating argument components and relations in persuasive essays. In ACL . 1501–1510
Christian Stab and Iryna Gurevych. 2014 · 2014
Cited alongside, same era.
Modeling user activity preference by leveraging user spatial temporal characteristics in LBSNs
Dingqi Yang, Daqing Zhang, Vincent W Zheng, and Zhiyong Yu. 2014 · 2014
Cited alongside, same era.
Patrick J Laub, Thomas Taimre, and Philip K Pollett. 2015 · 2015
Cited alongside, same era.
Data-driven activity prediction: Algorithms, evaluation methodology, and applications. In KDD . 805–814
Bryan Minor, Janardhan Rao Doppa, and Diane J Cook. 2015 · 2015
Cited alongside, same era.
Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon. 2016 · 2016
Cited alongside, same era.
Virtual-taobao: Virtualizing real-world online retail environment for reinforcement learning. In AAAI , Vol. 33. 4902–4909
Jing-Cheng Shi, Yang Yu, Qing Da, Shi-Yong Chen, and An-Xiang Zeng. 2019 · 2019
Later among the works it cites.
Unveiling taxi drivers’ strategies via cgail: Conditional generative adversarial imitation learning. In ICDM . IEEE, 1480–1485
Xin Zhang, Yanhua Li, Xun Zhou, and Jun Luo. 2019 · 2019
Later among the works it cites.
Learning to simulate human mobility. In KDD . 3426–3433
Jie Feng, Zeyu Yang, Fengli Xu, Haisu Yu, Mudan Wang, and Yong Li. 2020 · 2020
Later among the works it cites.
Prediction of human activities based on a new structure of skeleton features and deep learning model
Neziha Jaouedi, Francisco J Perales, José Maria Buades, Noureddine Boujnah, and Med Salim Bouhlel. 2020 · 2020
Later among the works it cites.
Location-based social network data generation based on patterns of life. In MDM . IEEE, 158–167
Joon-Seok Kim, Hyunjee Jin, Hamdi Kavak, Ovi Chris Rouly, Andrew Crooks, Dieter Pfoser, Carola Wenk, and Andreas Züfle. 2020 · 2020
Later among the works it cites.
Massive Cross-Platform Simulations of Online Social Networks. In AAMAS . 895–903
Goran Murić, Alexey Tregubov, Jim Blythe, Andrés Abeliuk, Divya Choudhary, Kristina Lerman, and Emilio Ferrara. 2020 · 2020
Later among the works it cites.
xGAIL: Explainable Generative Adversarial Imitation Learning for Explainable Human Decision Analysis. In KDD . 1334–1343
Menghai Pan, Weixiao Huang, Yanhua Li, Xun Zhou, and Jun Luo. 2020 · 2020
Later among the works it cites.
Transformer hawkes process. In ICML . PMLR, 11692–11702
Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, and Hongyuan Zha. 2020 · 2020
Later among the works it cites.
Modeling Trajectories with Neural Ordinary Differential Equations.. In IJCAI . 1498–1504
Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, and Roger Zimmermann. 2021 · 2021
Later among the works it cites.
How Do We Move: Modeling Human Movement with System Dynamics. In AAAI
Hua Wei, Dongkuan Xu, Junjie Liang, and Zhenhui Li. 2021 · 2021
Later among the works it cites.
ProActive: Self-attentive temporal point process flows for activity sequences. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 496–504
Vinayak Gupta and Srikanta Bedathur. 2022 · 2022
Later among the works it cites.
Activity Trajectory Generation via Modeling Spatiotemporal Dynamics. In KDD . 4752–4762
Yuan Yuan, Jingtao Ding, Huandong Wang, Depeng Jin, and Yong Li. 2022 · 2022
Later among the works it cites.