{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T18:51:27Z","timestamp":1764874287428,"version":"3.46.0"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62394332","U24B20171"],"award-info":[{"award-number":["62394332","U24B20171"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Project of Beijing Municipal Commission of Transport","award":["2025-KJC-03-005"],"award-info":[{"award-number":["2025-KJC-03-005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1109\/tmc.2025.3599925","type":"journal-article","created":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T18:17:54Z","timestamp":1755627474000},"page":"1027-1041","source":"Crossref","is-referenced-by-count":0,"title":["SigFormer: A Transformer for Signaling Data Augmentation via Location Reconstruction"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2906-4289","authenticated-orcid":false,"given":"Mingzhe","family":"Liu","sequence":"first","affiliation":[{"name":"Hangzhou International Innovation Institute, Beihang University, Hangzhou, China"}]},{"given":"Haiyang","family":"Jiang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Complex & Critical Software Environment (CCSE), Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8948-3103","authenticated-orcid":false,"given":"Tongyu","family":"Zhu","sequence":"additional","affiliation":[{"name":"Hangzhou International Innovation Institute, Beihang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0157-1716","authenticated-orcid":false,"given":"Leilei","family":"Sun","sequence":"additional","affiliation":[{"name":"Hangzhou International Innovation Institute, Beihang University, Hangzhou, China"}]},{"given":"Jibin","family":"Wang","sequence":"additional","affiliation":[{"name":"China Mobile Information Technology Center, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2811-8962","authenticated-orcid":false,"given":"Hao","family":"Sheng","sequence":"additional","affiliation":[{"name":"Hangzhou International Innovation Institute, Beihang University, Hangzhou, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/ijgi10080545"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3121551"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3131337"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s13753-023-00480-3"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3058599"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3582427"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.14778\/3632093.3632113"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557481"},{"article-title":"CKConv: Continuous kernel convolution for sequential data","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Romero","key":"ref9"},{"key":"ref10","first-page":"24261","article-title":"MLP-mixer: An all-MLP architecture for vision","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Tolstikhin"},{"key":"ref11","doi-asserted-by":"crossref","DOI":"10.1145\/2939672.2939785","article-title":"XGBoost: A scalable tree boosting system","volume-title":"Proc. 22nd ACM SIGKDD Int. Conf. Knowl. Discov. Data Mining","author":"Chen"},{"article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","year":"2018","author":"Bai","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2997967"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412190"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599533"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/s23020908"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-019-01318-w"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/ijgi9030140"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2016.08.007"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2019.101348"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2014.01.002"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.eastsj.2020.100025"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2020.105772"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.apgeog.2019.102103"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3390\/ijgi10060369"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/ijgi9060342"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.43481"},{"key":"ref28","first-page":"6776","article-title":"BRITS: Bidirectional recurrent imputation for time series","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Cao"},{"article-title":"Multi-time attention networks for irregularly sampled time series","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Shukla","key":"ref29"},{"key":"ref30","first-page":"11238","article-title":"NAOMI: Non-autoregressive multiresolution sequence imputation","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Liu"},{"article-title":"Filling the g_ap_s: Multivariate time series imputation by graph neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Cini","key":"ref31"},{"article-title":"Learning to reconstruct missing data from spatiotemporal graphs with sparse observations","year":"2022","author":"Marisca","key":"ref32"},{"article-title":"CDSA: Cross-dimensional self-attention for multivariate, geo-tagged time series imputation","year":"2019","author":"Ma","key":"ref33"},{"key":"ref34","first-page":"1651","article-title":"GP-VAE: Deep probabilistic time series imputation","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Fortuin"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3053599"},{"key":"ref36","first-page":"5689","article-title":"Gain: Missing data imputation using generative adversarial nets","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yoon"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/429"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17086"},{"key":"ref39","first-page":"24804","article-title":"CSDI: Conditional score-based diffusion models for probabilistic time series imputation","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Tashiro"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP55844.2023.10285980"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26310"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/414"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3516367"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7755\/11275706\/11129922.pdf?arnumber=11129922","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T18:39:20Z","timestamp":1764873560000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11129922\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":43,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tmc.2025.3599925","relation":{},"ISSN":["1536-1233","1558-0660","2161-9875"],"issn-type":[{"type":"print","value":"1536-1233"},{"type":"electronic","value":"1558-0660"},{"type":"electronic","value":"2161-9875"}],"subject":[],"published":{"date-parts":[[2026,1]]}}}