{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T16:48:41Z","timestamp":1765039721473,"version":"3.28.0"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T00:00:00Z","timestamp":1694908800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T00:00:00Z","timestamp":1694908800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,17]]},"DOI":"10.1109\/mlsp55844.2023.10285943","type":"proceedings-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T17:55:41Z","timestamp":1698083741000},"page":"1-6","source":"Crossref","is-referenced-by-count":2,"title":["A Time-Aware Tensor Decomposition for Tracking Evolving Patterns"],"prefix":"10.1109","author":[{"given":"Christos","family":"Chatzis","sequence":"first","affiliation":[{"name":"Simula Metropolitan Center for Digital Engineering,Oslo,Norway"}]},{"given":"Max","family":"Pfeffer","sequence":"additional","affiliation":[{"name":"Georg-August-Universit&#x00E4;t G&#x00F6;ttingen,Institute for Numerical and Applied Mathematics,G&#x00F6;ttingen,Germany"}]},{"given":"Pedro","family":"Lind","sequence":"additional","affiliation":[{"name":"OsloMet,Faculty of Technology, Art and Design,Oslo,Norway"}]},{"given":"Evrim","family":"Acar","sequence":"additional","affiliation":[{"name":"Simula Metropolitan Center for Digital Engineering,Oslo,Norway"}]}],"member":"263","reference":[{"key":"ref13","first-page":"327","article-title":"Identifying and alleviating concept drift in streaming tensor decomposition","author":"pasricha","year":"2018","journal-title":"ECML PKDD"},{"key":"ref12","first-page":"3863","article-title":"SSMF: shifting seasonal matrix factorization","volume":"34","author":"kawabata","year":"2021","journal-title":"NeurIPS"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1002\/cem.764"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/0024-3795(77)90069-6"},{"key":"ref14","first-page":"30","article-title":"PARAFAC2: Mathematical and technical notes","author":"harshman","year":"1972","journal-title":"UCLA Working Papers in Phonetics"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2876857"},{"key":"ref11","first-page":"3","article-title":"Temporally evolving community detection and prediction in content-centric networks","author":"appel","year":"2018","journal-title":"ECML PKDD"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.softx.2022.101292"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018669"},{"key":"ref21","first-page":"1","article-title":"TensorLy: Tensor Learning in Python","volume":"20","author":"kossaifi","year":"2019","journal-title":"JMLR"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-020-0660-7"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053902"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1099-128X(199905\/08)13:3\/4<275::AID-CEM543>3.0.CO;2-B"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1137\/07070111X","article-title":"Tensor decompositions and applications","volume":"51","author":"kolda","year":"2009","journal-title":"SIAM Review"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2576427"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1137\/21M1450033"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.146"},{"key":"ref7","first-page":"847","article-title":"Temporal regularized matrix factorization for high-dimensional time series prediction","author":"yu","year":"2016","journal-title":"NIPS"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-06059-7"},{"key":"ref4","first-page":"1","article-title":"Foundations of the PARAFAC procedure: Models and conditions for an &#x201C;explanatory&#x201D; multimodal factor analysis","volume":"16","author":"harshman","year":"1970","journal-title":"UCLA Working Papers in Phonetics"},{"key":"ref3","first-page":"147","article-title":"Discussion Tracking in Enron Email Using PARAFAC","author":"bader","year":"2007","journal-title":"Survey of Text Mining Clustering Classification and Retrieval"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1921632.1921636"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/BF02310791"}],"event":{"name":"2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)","start":{"date-parts":[[2023,9,17]]},"location":"Rome, Italy","end":{"date-parts":[[2023,9,20]]}},"container-title":["2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10285838\/10285858\/10285943.pdf?arnumber=10285943","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T19:03:39Z","timestamp":1699902219000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10285943\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,17]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/mlsp55844.2023.10285943","relation":{},"subject":[],"published":{"date-parts":[[2023,9,17]]}}}