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Achieving accurate imputation is critical to the operation of transportation networks. Existing approaches usually focus on the characteristic analysis of temporal variation and adjacent spatial representation, and the consideration of higher\u2010order spatial correlations and continuous data missing attracts more attentions from the academia and industry. In this paper, by leveraging motif\u2010based graph aggregation, we propose a spatiotemporal imputation approach to address the issue of traffic data missing. First, through motif discovery, the higher\u2010order graph aggregation model was presented in traffic networks. It utilized graph convolution network (GCN) to polymerize the correlated segment attributes of the missing data segments. Then, the multitime dimension imputation model based on bidirectional long short\u2010term memory (Bi\u2010LSTM) incorporated the recent, daily\u2010periodic, and weekly\u2010periodic dependencies of the historical data. Finally, the spatial aggregated values and the temporal fusion values were integrated to obtain the results. We conducted comprehensive experiments based on the real\u2010world dataset and discussed the case of random and continuous data missing by different time intervals, and the results showed that the proposed approach was feasible and accurate.<\/jats:p>","DOI":"10.1155\/2022\/1702170","type":"journal-article","created":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T10:50:14Z","timestamp":1642416614000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Higher\u2010Order Motif\u2010Based Spatiotemporal Graph Imputation Approach for Transportation Networks"],"prefix":"10.1155","volume":"2022","author":[{"given":"Difeng","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1064-1250","authenticated-orcid":false,"given":"Guojiang","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1737-3420","authenticated-orcid":false,"given":"Jingjing","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenfeng","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2698-3319","authenticated-orcid":false,"given":"Xiangjie","family":"Kong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,1,17]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2020.102730"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/s19224967"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3067324"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3016037"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/9354273"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2964299"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2018.07.018"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/4039758"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107114"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2018.2869768"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1049\/iet-its.2018.5114"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2018.01.015"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.05.033"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2020.102673"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2909038"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)0733-947X(2007)133:3(180)"},{"key":"e_1_2_9_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.07.069"},{"key":"e_1_2_9_18_2","doi-asserted-by":"crossref","unstructured":"AhnJ. 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