{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T15:02:06Z","timestamp":1776092526650,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":62,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671866","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:55:12Z","timestamp":1724561712000},"page":"4676-4687","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":34,"title":["ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5657-181X","authenticated-orcid":false,"given":"Yuanshao","family":"Zhu","sequence":"first","affiliation":[{"name":"Southern University of Science and Technology & City University of Hong Kong, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6392-6711","authenticated-orcid":false,"given":"James Jianqiao","family":"Yu","sequence":"additional","affiliation":[{"name":"University of York, York, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2926-4416","authenticated-orcid":false,"given":"Xiangyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0751-2602","authenticated-orcid":false,"given":"Qidong","family":"Liu","sequence":"additional","affiliation":[{"name":"Xi'an Jiao Tong University & City University of Hong Kong, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9782-218X","authenticated-orcid":false,"given":"Yongchao","family":"Ye","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2260-9079","authenticated-orcid":false,"given":"Wei","family":"Chen","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1194-8334","authenticated-orcid":false,"given":"Zijian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Jilin University & City University of Hong Kong, Jilin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4450-2251","authenticated-orcid":false,"given":"Xuetao","family":"Wei","sequence":"additional","affiliation":[{"name":"Southern University of Science and Technology, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2817-7337","authenticated-orcid":false,"given":"Yuxuan","family":"Liang","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (Guangzhou), Guanzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.physrep.2018.01.001"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467158"},{"key":"e_1_3_2_2_3_1","unstructured":"Wei Chen Yuxuan Liang Yuanshao Zhu Yanchuan Chang Kang Luo Haomin Wen Lei Li Yanwei Yu Qingsong Wen Chao Chen et al. 2024. Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond. arXiv preprint arXiv:2403.14151 (2024)."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467330"},{"key":"e_1_3_2_2_6_1","volume-title":"Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting","author":"Deng Jinliang","year":"2024","unstructured":"Jinliang Deng, Xiusi Chen, Renhe Jiang, Du Yin, Yi Yang, Xuan Song, and Ivor W Tsang. 2024. Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting. IEEE Transactions on Knowledge and Data Engineering (2024)."},{"key":"e_1_3_2_2_7_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_2_8_1","first-page":"8780","article-title":"Diffusion models beat gans on image synthesis","volume":"34","author":"Dhariwal Prafulla","year":"2021","unstructured":"Prafulla Dhariwal and Alexander Nichol. 2021. Diffusion models beat gans on image synthesis. Advances in Neural Information Processing Systems, Vol. 34 (2021), 8780--8794.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_9_1","unstructured":"Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai Thomas Unterthiner Mostafa Dehghani Matthias Minderer Georg Heigold Sylvain Gelly et al. 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)."},{"key":"e_1_3_2_2_10_1","volume-title":"LDPTrace: Locally Differentially Private Trajectory Synthesis. arXiv preprint arXiv:2302.06180","author":"Du Yuntao","year":"2023","unstructured":"Yuntao Du, Yujia Hu, Zhikun Zhang, Ziquan Fang, Lu Chen, Baihua Zheng, and Yunjun Gao. 2023. LDPTrace: Locally Differentially Private Trajectory Synthesis. arXiv preprint arXiv:2302.06180 (2023)."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-021-00652-x"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3412862"},{"key":"e_1_3_2_2_13_1","volume-title":"Advances in Neural Information Processing Systems","volume":"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. In Advances in Neural Information Processing Systems, Vol. 27."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2018.00100"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599528"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-33377-4_7"},{"key":"e_1_3_2_2_19_1","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems, Vol. 33 (2020), 6840--6851.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_20_1","volume-title":"Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning. arXiv preprint arXiv:2310.17360","author":"Hu Junfeng","year":"2023","unstructured":"Junfeng Hu, Xu Liu, Zhencheng Fan, Yuxuan Liang, and Roger Zimmermann. 2023. Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning. arXiv preprint arXiv:2310.17360 (2023)."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3538712.3543822"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482000"},{"key":"e_1_3_2_2_23_1","volume-title":"DiffWave: A Versatile Diffusion Model for Audio Synthesis. In International Conference on Learning Representations.","author":"Kong Zhifeng","year":"2020","unstructured":"Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro. 2020. DiffWave: A Versatile Diffusion Model for Audio Synthesis. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_24_1","volume-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting. arXiv preprint arXiv:1707.01926","author":"Li Yaguang","year":"2017","unstructured":"Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu. 2017. Diffusion convolutional recurrent neural network: Data-driven traffic forecasting. arXiv preprint arXiv:1707.01926 (2017)."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"crossref","unstructured":"Yuxuan Liang Kun Ouyang Hanshu Yan Yiwei Wang Zekun Tong and Roger Zimmermann. 2021. Modeling Trajectories with Neural Ordinary Differential Equations. In IJCAI. 1498--1504.","DOI":"10.24963\/ijcai.2021\/207"},{"key":"e_1_3_2_2_26_1","volume-title":"Foundation Models for Time Series Analysis: A Tutorial and Survey. arXiv preprint arXiv:2403.14735","author":"Liang Yuxuan","year":"2024","unstructured":"Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, and Qingsong Wen. 2024. Foundation Models for Time Series Analysis: A Tutorial and Survey. arXiv preprint arXiv:2403.14735 (2024)."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485125"},{"key":"e_1_3_2_2_28_1","volume-title":"Glide: Towards photorealistic image generation and editing with text-guided diffusion models. arXiv preprint arXiv:2112.10741","author":"Nichol Alex","year":"2021","unstructured":"Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen. 2021. Glide: Towards photorealistic image generation and editing with text-guided diffusion models. arXiv preprint arXiv:2112.10741 (2021)."},{"key":"e_1_3_2_2_29_1","unstructured":"OpenStreetMap contributors. 2017. Planet dump retrieved from https:\/\/planet.osm.org. https:\/\/www.openstreetmap.org."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/530"},{"key":"e_1_3_2_2_31_1","volume-title":"International conference on machine learning. PMLR, 8748--8763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748--8763."},{"key":"e_1_3_2_2_32_1","volume-title":"11th International Conference on Geographic Information Science (GIScience","author":"Rao Jinmeng","year":"2020","unstructured":"Jinmeng Rao, Song Gao, Yuhao Kang, and Qunying Huang. 2020. LSTM-TrajGAN: A Deep Learning Approach to Trajectory Privacy Protection. In 11th International Conference on Geographic Information Science (GIScience 2021)."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5435"},{"key":"e_1_3_2_2_36_1","volume-title":"A deep gravity model for mobility flows generation. Nature communications","author":"Simini Filippo","year":"2021","unstructured":"Filippo Simini, Gianni Barlacchi, Massimilano Luca, and Luca Pappalardo. 2021. A deep gravity model for mobility flows generation. Nature communications, Vol. 12, 1 (2021), 6576."},{"key":"e_1_3_2_2_37_1","volume-title":"International Conference on Machine Learning. PMLR, 2256--2265","author":"Sohl-Dickstein Jascha","year":"2015","unstructured":"Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli. 2015. Deep unsupervised learning using nonequilibrium thermodynamics. In International Conference on Machine Learning. PMLR, 2256--2265."},{"key":"e_1_3_2_2_38_1","volume-title":"Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502","author":"Song Jiaming","year":"2020","unstructured":"Jiaming Song, Chenlin Meng, and Stefano Ermon. 2020. Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502 (2020)."},{"key":"e_1_3_2_2_39_1","volume-title":"Attention is all you need. Advances in neural information processing systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, ?ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3440207"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.6339\/21-JDS1004"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219900"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00065"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589132.3625614"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/264"},{"key":"e_1_3_2_2_46_1","volume-title":"trajGANs: using generative adversarial networks for geo-privacy protection of trajectory data. Vision paper","author":"Xi Liu","year":"2018","unstructured":"Liu Xi, Chen Hanzhou, and Andris Clio. 2018. trajGANs: using generative adversarial networks for geo-privacy protection of trajectory data. Vision paper (2018)."},{"key":"e_1_3_2_2_47_1","volume-title":"DeepRailway: A Deep Learning System for Forecasting Railway Traffic. In 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). 51--56","author":"Xia Tianqi","year":"2018","unstructured":"Tianqi Xia, Xuan Song, Zipei Fan, Hiroshi Kanasugi, QuanJun Chen, Renhe Jiang, and Ryosuke Shibasaki. 2018. DeepRailway: A Deep Learning System for Forecasting Railway Traffic. In 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). 51--56."},{"key":"e_1_3_2_2_48_1","volume-title":"Proc. 9th Int. Conf. Learn. Represent. 1--9.","author":"Xu Nan","year":"2021","unstructured":"Nan Xu, Loc Trinh, Sirisha Rambhatla, Zhen Zeng, Jiahao Chen, Samuel Assefa, and Yan Liu. 2021. Simulating continuous-time human mobility trajectories. In Proc. 9th Int. Conf. Learn. Represent. 1--9."},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939799"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539360"},{"key":"e_1_3_2_2_51_1","volume-title":"Diffusion models: A comprehensive survey of methods and applications. arXiv preprint arXiv:2209.00796","author":"Yang Ling","year":"2022","unstructured":"Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang, Bin Cui, and Ming-Hsuan Yang. 2022. Diffusion models: A comprehensive survey of methods and applications. arXiv preprint arXiv:2209.00796 (2022)."},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3207894"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3542671"},{"key":"e_1_3_2_2_54_1","volume-title":"Ensuring confidentiality of geocoded health data: assessing geographic masking strategies for individual-level data. Advances in medicine","author":"Zandbergen Paul A","year":"2014","unstructured":"Paul A Zandbergen. 2014. Ensuring confidentiality of geocoded health data: assessing geographic masking strategies for individual-level data. Advances in medicine, Vol. 2014 (2014)."},{"key":"e_1_3_2_2_55_1","volume-title":"DP-TrajGAN: A privacy-aware trajectory generation model with differential privacy. Future Generation Computer Systems","author":"Zhang Jing","year":"2022","unstructured":"Jing Zhang, Qihan Huang, Yirui Huang, Qian Ding, and Pei-Wei Tsai. 2022. DP-TrajGAN: A privacy-aware trajectory generation model with differential privacy. Future Generation Computer Systems (2022)."},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3133024"},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3229329.3229331"},{"key":"e_1_3_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.158"},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/2743025"},{"key":"e_1_3_2_2_60_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2629592","article-title":"Urban computing: concepts, methodologies, and applications","volume":"5","author":"Zheng Yu","year":"2014","unstructured":"Yu Zheng, Licia Capra, Ouri Wolfson, and Hai Yang. 2014. Urban computing: concepts, methodologies, and applications. ACM Transactions on Intelligent Systems and Technology (TIST), Vol. 5, 3 (2014), 1--55.","journal-title":"ACM Transactions on Intelligent Systems and Technology (TIST)"},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3092015"},{"key":"e_1_3_2_2_62_1","volume-title":"DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model. In Thirty-seventh Conference on Neural Information Processing Systems.","author":"Zhu Yuanshao","year":"2023","unstructured":"Yuanshao Zhu, Yongchao Ye, Shiyao Zhang, Xiangyu Zhao, and James Jianqiao Yu. 2023. DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model. In Thirty-seventh Conference on Neural Information Processing Systems."}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Barcelona Spain","acronym":"KDD '24","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 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671866","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671866","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:04:14Z","timestamp":1750291454000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671866"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":62,"alternative-id":["10.1145\/3637528.3671866","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671866","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}