{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T05:27:11Z","timestamp":1663997231998},"publisher-location":"New York, NY, USA","reference-count":55,"publisher":"ACM","funder":[{"name":"The National Nature Science Foundation of China","award":["61971267 61972223 62171260 U1936217"]},{"name":"The National Key Research and Development Program","award":["2020YFA0711403"]},{"name":"Young Elite Scientists Sponsorship Program by CIC","award":["2021QNRC001"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,14]]},"DOI":"10.1145\/3534678.3542671","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:12Z","timestamp":1660331172000},"source":"Crossref","is-referenced-by-count":0,"title":["Activity Trajectory Generation via Modeling Spatiotemporal Dynamics"],"prefix":"10.1145","author":[{"given":"Yuan","family":"Yuan","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Jingtao","family":"Ding","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Huandong","family":"Wang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Depeng","family":"Jin","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Yong","family":"Li","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Yelp dataset challenge: Review rating prediction. arXiv preprint arXiv:1605.05362","author":"Asghar Nabiha","year":"2016","unstructured":"Nabiha Asghar . 2016. Yelp dataset challenge: Review rating prediction. arXiv preprint arXiv:1605.05362 ( 2016 ). Nabiha Asghar. 2016. Yelp dataset challenge: Review rating prediction. arXiv preprint arXiv:1605.05362 (2016)."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/72.536317"},{"key":"e_1_3_2_2_3_1","volume-title":"Neural spatiotemporal point processes. arXiv preprint arXiv:2011.04583","author":"Chen Ricky TQ","year":"2020","unstructured":"Ricky TQ Chen , Brandon Amos , and Maximilian Nickel . 2020. Neural spatiotemporal point processes. arXiv preprint arXiv:2011.04583 ( 2020 ). Ricky TQ Chen, Brandon Amos, and Maximilian Nickel. 2020. Neural spatiotemporal point processes. arXiv preprint arXiv:2011.04583 (2020)."},{"key":"e_1_3_2_2_4_1","volume-title":"Neural ordinary differential equations. NIPS 31","author":"Chen Ricky TQ","year":"2018","unstructured":"Ricky TQ Chen , Yulia Rubanova , Jesse Bettencourt , and David K Duvenaud . 2018. Neural ordinary differential equations. NIPS 31 ( 2018 ). Ricky TQ Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud. 2018. Neural ordinary differential equations. NIPS 31 (2018)."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2021.103091"},{"key":"e_1_3_2_2_6_1","first-page":"1","article-title":"Spatio-temporal point processes: methods and applications","volume":"107","author":"Diggle Peter J","year":"2006","unstructured":"Peter J Diggle . 2006 . Spatio-temporal point processes: methods and applications . Monographs on Statistics and Applied Probability 107 (2006), 1 . Peter J Diggle. 2006. Spatio-temporal point processes: methods and applications. Monographs on Statistics and Applied Probability 107 (2006), 1.","journal-title":"Monographs on Statistics and Applied Probability"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"crossref","unstructured":"Zheng Fang Qingqing Long Guojie Song and Kunqing Xie. 2021. Spatialtemporal graph ode networks for traffic flow forecasting. In KDD. 364--373. Zheng Fang Qingqing Long Guojie Song and Kunqing Xie. 2021. Spatialtemporal graph ode networks for traffic flow forecasting. In KDD. 364--373.","DOI":"10.1145\/3447548.3467430"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186058"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"crossref","unstructured":"Jie Feng Zeyu Yang Fengli Xu Haisu Yu Mudan Wang and Yong Li. 2020. Learning to simulate human mobility. In KDD. 3426--3433. Jie Feng Zeyu Yang Fengli Xu Haisu Yu Mudan Wang and Yong Li. 2020. Learning to simulate human mobility. In KDD. 3426--3433.","DOI":"10.1145\/3394486.3412862"},{"key":"e_1_3_2_2_10_1","volume-title":"The hierarchical hidden Markov model: Analysis and applications. Machine learning 32, 1","author":"Fine Shai","year":"1998","unstructured":"Shai Fine , Yoram Singer , and Naftali Tishby . 1998. The hierarchical hidden Markov model: Analysis and applications. Machine learning 32, 1 ( 1998 ), 41--62. Shai Fine, Yoram Singer, and Naftali Tishby. 1998. The hierarchical hidden Markov model: Analysis and applications. Machine learning 32, 1 (1998), 41--62."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2004.1365067"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313610"},{"key":"e_1_3_2_2_13_1","volume-title":"Generative adversarial nets. Advances in neural information processing systems 27","author":"Goodfellow Ian","year":"2014","unstructured":"Ian Goodfellow , Jean Pouget-Abadie , Mehdi Mirza , Bing Xu , David Warde-Farley , Sherjil Ozair , Aaron Courville , and Yoshua Bengio . 2014. Generative adversarial nets. Advances in neural information processing systems 27 ( 2014 ). Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative adversarial nets. Advances in neural information processing systems 27 (2014)."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11829"},{"key":"e_1_3_2_2_15_1","volume-title":"Generative adversarial imitation learning. Advances in neural information processing systems 29","author":"Ho Jonathan","year":"2016","unstructured":"Jonathan Ho and Stefano Ermon . 2016. Generative adversarial imitation learning. Advances in neural information processing systems 29 ( 2016 ). Jonathan Ho and Stefano Ermon. 2016. Generative adversarial imitation learning. Advances in neural information processing systems 29 (2016)."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0191-2615(03)00007-9"},{"key":"e_1_3_2_2_17_1","volume-title":"Bidirectional LSTM-CRF models for sequence tagging. arXiv preprint arXiv:1508.01991","author":"Huang Zhiheng","year":"2015","unstructured":"Zhiheng Huang , Wei Xu , and Kai Yu. 2015. Bidirectional LSTM-CRF models for sequence tagging. arXiv preprint arXiv:1508.01991 ( 2015 ). Zhiheng Huang, Wei Xu, and Kai Yu. 2015. Bidirectional LSTM-CRF models for sequence tagging. arXiv preprint arXiv:1508.01991 (2015)."},{"key":"e_1_3_2_2_18_1","volume-title":"Neural jump stochastic differential equations. Advances in Neural Information Processing Systems 32","author":"Jia Junteng","year":"2019","unstructured":"Junteng Jia and Austin R Benson . 2019. Neural jump stochastic differential equations. Advances in Neural Information Processing Systems 32 ( 2019 ). Junteng Jia and Austin R Benson. 2019. Neural jump stochastic differential equations. Advances in Neural Information Processing Systems 32 (2019)."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1524261113"},{"key":"e_1_3_2_2_20_1","volume-title":"Differential equations and mathematical biology","author":"Jones Douglas Samuel","unstructured":"Douglas Samuel Jones , Michael Plank , and Brian D Sleeman . 2009. Differential equations and mathematical biology . Chapman and Hall\/CRC. Douglas Samuel Jones, Michael Plank, and Brian D Sleeman. 2009. Differential equations and mathematical biology. Chapman and Hall\/CRC."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ypmed.2010.07.019"},{"key":"e_1_3_2_2_22_1","first-page":"2060","article-title":"Prediction model of user physical activity using data characteristics-based long short-term memory recurrent neural networks","volume":"13","author":"Kim Joo-Chang","year":"2019","unstructured":"Joo-Chang Kim and Kyungyong Chung . 2019 . Prediction model of user physical activity using data characteristics-based long short-term memory recurrent neural networks . TIIS 13 , 4 (2019), 2060 -- 2077 . Joo-Chang Kim and Kyungyong Chung. 2019. Prediction model of user physical activity using data characteristics-based long short-term memory recurrent neural networks. TIIS 13, 4 (2019), 2060--2077.","journal-title":"TIIS"},{"key":"e_1_3_2_2_23_1","volume-title":"Andrew Crooks, Dieter Pfoser, Carola Wenk, and Andreas Z\u00fcfle.","author":"Kim Joon-Seok","year":"2020","unstructured":"Joon-Seok Kim , Hyunjee Jin , Hamdi Kavak , Ovi Chris Rouly , Andrew Crooks, Dieter Pfoser, Carola Wenk, and Andreas Z\u00fcfle. 2020 . 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 Z\u00fcfle. 2020. Location-based social network data generation based on patterns of life. In MDM. IEEE, 158--167."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01097184"},{"key":"e_1_3_2_2_25_1","volume-title":"Precision epidemiology for infectious disease control. Nature medicine 25, 2","author":"Ladner Jason T","year":"2019","unstructured":"Jason T Ladner , Nathan D Grubaugh , Oliver G Pybus , and Kristian G Andersen . 2019. Precision epidemiology for infectious disease control. Nature medicine 25, 2 ( 2019 ), 206--211. Jason T Ladner, Nathan D Grubaugh, Oliver G Pybus, and Kristian G Andersen. 2019. Precision epidemiology for infectious disease control. Nature medicine 25, 2 (2019), 206--211."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Shengjie Lai Nick W Ruktanonchai Liangcai Zhou Olivia Prosper Wei Luo Jessica R Floyd Amy Wesolowski Mauricio Santillana Chi Zhang Xiangjun Du etal 2020. Effect of non-pharmaceutical interventions to contain COVID-19 in China. nature 585 7825 (2020) 410--413. Shengjie Lai Nick W Ruktanonchai Liangcai Zhou Olivia Prosper Wei Luo Jessica R Floyd Amy Wesolowski Mauricio Santillana Chi Zhang Xiangjun Du et al. 2020. Effect of non-pharmaceutical interventions to contain COVID-19 in China. nature 585 7825 (2020) 410--413.","DOI":"10.1038\/s41586-020-2293-x"},{"key":"e_1_3_2_2_27_1","volume-title":"Systems of nonlinear partial differential equations: applications to biology and engineering","author":"Leung Anthony W","unstructured":"Anthony W Leung . 2013. Systems of nonlinear partial differential equations: applications to biology and engineering . Vol. 49 . Springer Science & Business Media . Anthony W Leung. 2013. Systems of nonlinear partial differential equations: applications to biology and engineering. Vol. 49. Springer Science & Business Media."},{"key":"e_1_3_2_2_28_1","volume-title":"POI recommendation of location-based social networks using tensor factorization","author":"Liao Guoqiong","unstructured":"Guoqiong Liao , Shan Jiang , Zhiheng Zhou , ChangxuanWan, and Xiping Liu . 2018. POI recommendation of location-based social networks using tensor factorization . In MDM. IEEE , 116--124. Guoqiong Liao, Shan Jiang, Zhiheng Zhou, ChangxuanWan, and Xiping Liu. 2018. POI recommendation of location-based social networks using tensor factorization. In MDM. IEEE, 116--124."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.9971"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2370216.2370423"},{"key":"e_1_3_2_2_31_1","volume-title":"Pde-net: Learning pdes from data. In ICML. PMLR, 3208--3216.","author":"Long Zichao","year":"2018","unstructured":"Zichao Long , Yiping Lu , Xianzhong Ma , and Bin Dong . 2018 . Pde-net: Learning pdes from data. In ICML. PMLR, 3208--3216. Zichao Long, Yiping Lu, Xianzhong Ma, and Bin Dong. 2018. Pde-net: Learning pdes from data. In ICML. PMLR, 3208--3216."},{"key":"e_1_3_2_2_32_1","volume-title":"Proceedings of the Conference on Differential and Difference Equations and Applications. Hindawi Publishing Corporation New York, 74--82","author":"Maksimov VP","year":"2006","unstructured":"VP Maksimov . 2006 . Theory of functional differential equations and some problems in economic dynamics . In Proceedings of the Conference on Differential and Difference Equations and Applications. Hindawi Publishing Corporation New York, 74--82 . VP Maksimov. 2006. Theory of functional differential equations and some problems in economic dynamics. In Proceedings of the Conference on Differential and Difference Equations and Applications. Hindawi Publishing Corporation New York, 74--82."},{"key":"e_1_3_2_2_33_1","volume-title":"Riemannian continuous normalizing flows. arXiv preprint arXiv:2006.10605","author":"Mathieu Emile","year":"2020","unstructured":"Emile Mathieu and Maximilian Nickel . 2020. Riemannian continuous normalizing flows. arXiv preprint arXiv:2006.10605 ( 2020 ). Emile Mathieu and Maximilian Nickel. 2020. Riemannian continuous normalizing flows. arXiv preprint arXiv:2006.10605 (2020)."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1137\/S0036141002409167"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1140\/epjb\/s10051-021-00222-8"},{"key":"e_1_3_2_2_36_1","volume-title":"Mining user mobility features for next place prediction in location-based services","author":"Noulas Anastasios","unstructured":"Anastasios Noulas , Salvatore Scellato , Neal Lathia , and Cecilia Mascolo . 2012. Mining user mobility features for next place prediction in location-based services . In ICDM. IEEE , 1038--1043. Anastasios Noulas, Salvatore Scellato, Neal Lathia, and Cecilia Mascolo. 2012. Mining user mobility features for next place prediction in location-based services. In ICDM. IEEE, 1038--1043."},{"key":"e_1_3_2_2_37_1","first-page":"570","article-title":"An empirical study of geographic user activity patterns in foursquare","volume":"5","author":"Noulas Anastasios","year":"2011","unstructured":"Anastasios Noulas , Salvatore Scellato , Cecilia Mascolo , and Massimiliano Pontil . 2011 . An empirical study of geographic user activity patterns in foursquare . In ICWSM , Vol. 5. 570 -- 573 . Anastasios Noulas, Salvatore Scellato, Cecilia Mascolo, and Massimiliano Pontil. 2011. An empirical study of geographic user activity patterns in foursquare. In ICWSM, Vol. 5. 570--573.","journal-title":"ICWSM"},{"key":"e_1_3_2_2_38_1","first-page":"32","article-title":"Exploiting semantic annotations for clustering geographic areas and users in location-based social networks","volume":"5","author":"Noulas Anastasios","year":"2011","unstructured":"Anastasios Noulas , Salvatore Scellato , Cecilia Mascolo , and Massimiliano Pontil . 2011 . Exploiting semantic annotations for clustering geographic areas and users in location-based social networks . In ICWSM , Vol. 5. 32 -- 35 . Anastasios Noulas, Salvatore Scellato, Cecilia Mascolo, and Massimiliano Pontil. 2011. Exploiting semantic annotations for clustering geographic areas and users in location-based social networks. In ICWSM, Vol. 5. 32--35.","journal-title":"ICWSM"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"crossref","unstructured":"Kun Ouyang Reza Shokri David S Rosenblum and Wenzhuo Yang. 2018. A Non-Parametric Generative Model for Human Trajectories.. In IJCAI. 3812--3817. Kun Ouyang Reza Shokri David S Rosenblum and Wenzhuo Yang. 2018. A Non-Parametric Generative Model for Human Trajectories.. In IJCAI. 3812--3817.","DOI":"10.24963\/ijcai.2018\/530"},{"key":"e_1_3_2_2_40_1","unstructured":"Menghai Pan Weixiao Huang Yanhua Li Xun Zhou and Jun Luo. 2020. 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. xgail: Explainable generative adversarial imitation learning for explainable human decision analysis. In KDD. 1334--1343."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Yukun Ping Chen Gao Taichi Liu Xiaoyi Du Hengliang Luo Depeng Jin and Yong Li. 2021. User Consumption Intention Prediction in Meituan. In KDD. 3472--3482. Yukun Ping Chen Gao Taichi Liu Xiaoyi Du Hengliang Luo Depeng Jin and Yong Li. 2021. User Consumption Intention Prediction in Meituan. In KDD. 3472--3482.","DOI":"10.1145\/3447548.3467178"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.5555\/3291125.3291150"},{"key":"e_1_3_2_2_43_1","volume-title":"Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347","author":"Schulman John","year":"2017","unstructured":"John Schulman , Filip Wolski , Prafulla Dhariwal , Alec Radford , and Oleg Klimov . 2017. Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347 ( 2017 ). John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017. Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347 (2017)."},{"key":"e_1_3_2_2_44_1","unstructured":"Varun Shankar Gavin D Portwood Arvind T Mohan Peetak P Mitra Christopher Rackauckas Lucas A Wilson David Schmidt and Venkatasubramanian Viswanathan. 2020. Learning non-linear spatio-temporal dynamics with convolutional Neural ODEs. In NeurIPS. Varun Shankar Gavin D Portwood Arvind T Mohan Peetak P Mitra Christopher Rackauckas Lucas A Wilson David Schmidt and Venkatasubramanian Viswanathan. 2020. Learning non-linear spatio-temporal dynamics with convolutional Neural ODEs. In NeurIPS."},{"key":"e_1_3_2_2_45_1","volume-title":"Modelling the scaling properties of human mobility. Nature physics 6, 10","author":"Song Chaoming","year":"2010","unstructured":"Chaoming Song , Tal Koren , PuWang, and Albert-L\u00e1szl\u00f3 Barab\u00e1si . 2010. Modelling the scaling properties of human mobility. Nature physics 6, 10 ( 2010 ), 818--823. Chaoming Song, Tal Koren, PuWang, and Albert-L\u00e1szl\u00f3 Barab\u00e1si. 2010. Modelling the scaling properties of human mobility. Nature physics 6, 10 (2010), 818--823."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmv.27643"},{"key":"e_1_3_2_2_47_1","volume-title":"Prevalent co-visiting patterns mining from location-based social networks","author":"Wang Xiaoxuan","unstructured":"Xiaoxuan Wang , Lizhen Wang , and Peizhong Yang . 2019. Prevalent co-visiting patterns mining from location-based social networks . In MDM. IEEE , 581--586. Xiaoxuan Wang, Lizhen Wang, and Peizhong Yang. 2019. Prevalent co-visiting patterns mining from location-based social networks. In MDM. IEEE, 581--586."},{"key":"e_1_3_2_2_48_1","unstructured":"YichenWang Evangelos Theodorou Apurv Verma and Le Song. 2018. A stochastic differential equation framework for guiding online user activities in closed loop. In AISTATS. PMLR 1077--1086. YichenWang Evangelos Theodorou Apurv Verma and Le Song. 2018. A stochastic differential equation framework for guiding online user activities in closed loop. In AISTATS. PMLR 1077--1086."},{"key":"e_1_3_2_2_49_1","volume-title":"Maximum likelihood estimation of misspecified models. Econometrica: Journal of the econometric society","author":"White Halbert","year":"1982","unstructured":"Halbert White . 1982. Maximum likelihood estimation of misspecified models. Econometrica: Journal of the econometric society ( 1982 ), 1--25. Halbert White. 1982. Maximum likelihood estimation of misspecified models. Econometrica: Journal of the econometric society (1982), 1--25."},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"crossref","unstructured":"Dingqi Yang Bingqing Qu Jie Yang and Philippe Cudre-Mauroux. 2019. Revisiting user mobility and social relationships in lbsns: a hypergraph embedding approach. In The world wide web conference. 2147--2157. Dingqi Yang Bingqing Qu Jie Yang and Philippe Cudre-Mauroux. 2019. Revisiting user mobility and social relationships in lbsns: a hypergraph embedding approach. In The world wide web conference. 2147--2157.","DOI":"10.1145\/3308558.3313635"},{"key":"e_1_3_2_2_51_1","article-title":"Modeling user activity preference by leveraging user spatial temporal characteristics in LBSNs","volume":"45","author":"Yang Dingqi","year":"2014","unstructured":"Dingqi Yang , Daqing Zhang , Vincent W Zheng , and Zhiyong Yu . 2014 . Modeling user activity preference by leveraging user spatial temporal characteristics in LBSNs . IEEE Transactions on Systems, Man, and Cybernetics: Systems 45 , 1 (2014). Dingqi Yang, Daqing Zhang, Vincent W Zheng, and Zhiyong Yu. 2014. Modeling user activity preference by leveraging user spatial temporal characteristics in LBSNs. IEEE Transactions on Systems, Man, and Cybernetics: Systems 45, 1 (2014).","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"key":"e_1_3_2_2_52_1","volume-title":"What's your next move: User activity prediction in location-based social networks","author":"Ye Jihang","unstructured":"Jihang Ye , Zhe Zhu , and Hong Cheng . 2013. What's your next move: User activity prediction in location-based social networks . In ICDM. SIAM , 171--179. Jihang Ye, Zhe Zhu, and Hong Cheng. 2013. What's your next move: User activity prediction in location-based social networks. In ICDM. SIAM, 171--179."},{"key":"e_1_3_2_2_53_1","first-page":"1682","article-title":"A generative model of urban activities from cellular data","volume":"19","author":"Yin Mogeng","year":"2017","unstructured":"Mogeng Yin , Madeleine Sheehan , Sidney Feygin , Jean-Fran\u00e7ois Paiement , and Alexei Pozdnoukhov . 2017 . A generative model of urban activities from cellular data . IEEE TITS 19 , 6 (2017), 1682 -- 1696 . Mogeng Yin, Madeleine Sheehan, Sidney Feygin, Jean-Fran\u00e7ois Paiement, and Alexei Pozdnoukhov. 2017. A generative model of urban activities from cellular data. IEEE TITS 19, 6 (2017), 1682--1696.","journal-title":"IEEE TITS"},{"key":"e_1_3_2_2_54_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10804"},{"key":"e_1_3_2_2_55_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12316"}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Washington DC USA","acronym":"KDD '22","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3542671","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,23]],"date-time":"2022-09-23T13:21:09Z","timestamp":1663939269000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3542671"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":55,"alternative-id":["10.1145\/3534678.3542671","10.1145\/3534678"],"URL":"http:\/\/dx.doi.org\/10.1145\/3534678.3542671","relation":{},"published":{"date-parts":[[2022,8,14]]}}}