{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T10:48:25Z","timestamp":1783334905405,"version":"3.54.6"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,4,30]],"date-time":"2023-04-30T00:00:00Z","timestamp":1682812800000},"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":[[2023,4,30]]},"DOI":"10.1145\/3543507.3583991","type":"proceedings-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T23:30:25Z","timestamp":1682551825000},"page":"2655-2665","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Learning Social Meta-knowledge for Nowcasting Human Mobility in Disaster"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2593-4638","authenticated-orcid":false,"given":"Renhe","family":"Jiang","sequence":"first","affiliation":[{"name":"The University of Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2613-9727","authenticated-orcid":false,"given":"Zhaonan","family":"Wang","sequence":"additional","affiliation":[{"name":"The University of Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0116-3878","authenticated-orcid":false,"given":"Yudong","family":"Tao","sequence":"additional","affiliation":[{"name":"University of Miami, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8504-0057","authenticated-orcid":false,"given":"Chuang","family":"Yang","sequence":"additional","affiliation":[{"name":"The University of Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4042-7888","authenticated-orcid":false,"given":"Xuan","family":"Song","sequence":"additional","affiliation":[{"name":"The University of Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8760-244X","authenticated-orcid":false,"given":"Ryosuke","family":"Shibasaki","sequence":"additional","affiliation":[{"name":"The University of Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9209-390X","authenticated-orcid":false,"given":"Shu-Ching","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Missouri-Kansas City, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0902-0844","authenticated-orcid":false,"given":"Mei-Ling","family":"Shyu","sequence":"additional","affiliation":[{"name":"University of Missouri-Kansas City, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,4,30]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397536.3422219"},{"key":"e_1_3_2_1_2_1","volume-title":"Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473","author":"Bahdanau Dzmitry","year":"2014","unstructured":"Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)."},{"key":"e_1_3_2_1_3_1","volume-title":"Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting. In 34th Conference on Neural Information Processing Systems.","author":"Bai Lei","year":"2020","unstructured":"Lei Bai, Lina Yao, Can Li, Xianzhi Wang, and Can Wang. 2020. Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting. In 34th Conference on Neural Information Processing Systems."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397536.3422261"},{"key":"e_1_3_2_1_5_1","unstructured":"Micha\u00ebl Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In Advances in neural information processing systems. 3844\u20133852."},{"key":"e_1_3_2_1_6_1","volume-title":"Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting. In The Thirty-Third AAAI Conference on Artificial Intelligence. AAAI Press, 890\u2013897","author":"Diao Zulong","year":"2019","unstructured":"Zulong Diao, Xin Wang, Dafang Zhang, Yingru Liu, Kun Xie, and Shaoyao He. 2019. Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting. In The Thirty-Third AAAI Conference on Artificial Intelligence. AAAI Press, 890\u2013897."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3264915"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00179"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341161.3342870"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983886"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313730"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3478099"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3472300"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11338"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330654"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86514-6_20"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482000"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210006"},{"key":"e_1_3_2_1_20_1","volume-title":"Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. In International Conference on Learning Representations.","author":"Li Yaguang","year":"2018","unstructured":"Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu. 2018. Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411920"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330884"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357832"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01438"},{"key":"e_1_3_2_1_25_1","volume-title":"Predicting traffic demand during hurricane evacuation using Real-time data from transportation systems and social media. Transportation research part C: emerging technologies 131","author":"Roy Kamol\u00a0Chandra","year":"2021","unstructured":"Kamol\u00a0Chandra Roy, Samiul Hasan, Aron Culotta, and Naveen Eluru. 2021. Predicting traffic demand during hurricane evacuation using Real-time data from transportation systems and social media. Transportation research part C: emerging technologies 131 (2021), 103339."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772777"},{"key":"e_1_3_2_1_27_1","volume-title":"Laying the Foundations of Deep Long-Term Crowd Flow Prediction. In 16th European Conference on Computer Vision(Lecture Notes in Computer Science, Vol.\u00a012374)","author":"Sohn S.","year":"2020","unstructured":"Samuel\u00a0S. Sohn, Honglu Zhou, Seonghyeon Moon, Sejong Yoon, Vladimir Pavlovic, and Mubbasir Kapadia. 2020. Laying the Foundations of Deep Long-Term Crowd Flow Prediction. In 16th European Conference on Computer Vision(Lecture Notes in Computer Science, Vol.\u00a012374). Springer, 711\u2013728."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.5555\/2887007.2887109"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1214\/14-AOS1255"},{"key":"e_1_3_2_1_30_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan\u00a0N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998\u20136008."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380186"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20342"},{"key":"e_1_3_2_1_33_1","unstructured":"YABAI Writers. 2017. Japan 47 Prefectures. http:\/\/yabai.com\/p\/2098."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-71246-8_38"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403118"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Zonghan Wu Shirui Pan Guodong Long Jing Jiang and Chengqi Zhang. 2019. Graph wavenet for deep spatial-temporal graph modeling. In IJCAI. 1907\u20131913.","DOI":"10.24963\/ijcai.2019\/264"},{"key":"e_1_3_2_1_37_1","volume-title":"Spatial-temporal transformer networks for traffic flow forecasting. arXiv preprint arXiv:2001.02908","author":"Xu Mingxing","year":"2020","unstructured":"Mingxing Xu, Wenrui Dai, Chunmiao Liu, Xing Gao, Weiyao Lin, Guo-Jun Qi, and Hongkai Xiong. 2020. Spatial-temporal transformer networks for traffic flow forecasting. arXiv preprint arXiv:2001.02908 (2020)."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330697"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3191786"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10735"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/837"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5477"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159682"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"crossref","unstructured":"Ali Zonoozi Jung-jae Kim Xiao-Li Li and Gao Cong. 2018. Periodic-CRN: A Convolutional Recurrent Model for Crowd Density Prediction with Recurring Periodic Patterns.. In IJCAI. 3732\u20133738.","DOI":"10.24963\/ijcai.2018\/519"}],"event":{"name":"WWW '23: The ACM Web Conference 2023","location":"Austin TX USA","acronym":"WWW '23","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2023"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583991","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3543507.3583991","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:00:47Z","timestamp":1750186847000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583991"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,30]]},"references-count":45,"alternative-id":["10.1145\/3543507.3583991","10.1145\/3543507"],"URL":"https:\/\/doi.org\/10.1145\/3543507.3583991","relation":{},"subject":[],"published":{"date-parts":[[2023,4,30]]},"assertion":[{"value":"2023-04-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}