{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:32:29Z","timestamp":1723015949400},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:p>Real-world spatio-temporal data is often incomplete or inaccurate due to various data loading delays. For example, a location-disease-time tensor of case counts can have multiple delayed updates of recent temporal slices for some locations or diseases. Recovering such missing or noisy (under-reported) elements of the input tensor can be viewed as a generalized tensor completion problem. Existing tensor completion methods usually assume that i) missing elements are randomly distributed and ii) noise for each tensor element is i.i.d. zero-mean. Both assumptions can be violated for spatio-temporal tensor data. We often observe multiple versions of the input tensor with different under-reporting noise levels. The amount of noise can be time- or location-dependent as more updates are progressively introduced to the tensor. We model such dynamic data as a multi-version tensor with an extra tensor mode capturing the data updates. We propose a low-rank tensor model to predict the updates over time. We demonstrate that our method can accurately predict the ground-truth values of many real-world tensors. We obtain up to  27.2%  lower root mean-squared-error compared to the best baseline method. Finally, we extend our method to track the tensor data over time, leading to significant computational savings.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/400","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"2906-2912","source":"Crossref","is-referenced-by-count":0,"title":["Multi-version Tensor Completion for Time-delayed Spatio-temporal Data"],"prefix":"10.24963","author":[{"given":"Cheng","family":"Qian","sequence":"first","affiliation":[{"name":"Analytics Center of Excellence, IQVIA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nikos","family":"Kargas","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Minnesota Twin Cities"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cao","family":"Xiao","sequence":"additional","affiliation":[{"name":"Analytics Center of Excellence, IQVIA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucas","family":"Glass","sequence":"additional","affiliation":[{"name":"Analytics Center of Excellence, IQVIA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas","family":"Sidiropoulos","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Virginia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jimeng","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois Urbana-Champaign"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2021","name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","start":{"date-parts":[[2021,8,19]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:03:04Z","timestamp":1628679784000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/400"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/400","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}