{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:21:32Z","timestamp":1792786892024,"version":"4.5.0"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"NSF IIS","award":["1651902"],"award-info":[{"award-number":["1651902"]}]},{"DOI":"10.13039\/100000183","name":"U.S. Army Research Office","doi-asserted-by":"publisher","award":["W911NF-17-1-0367"],"award-info":[{"award-number":["W911NF-17-1-0367"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2021,6,1]]},"DOI":"10.1109\/tkde.2019.2954317","type":"journal-article","created":{"date-parts":[[2019,11,19]],"date-time":"2019-11-19T16:04:25Z","timestamp":1574179465000},"page":"2369-2379","source":"Crossref","is-referenced-by-count":76,"title":["Clustering With Outlier Removal"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0821-8640","authenticated-orcid":false,"given":"Hongfu","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5845-8602","authenticated-orcid":false,"given":"Jun","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5098-2853","authenticated-orcid":false,"given":"Yun","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939813"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623676"},{"key":"ref33","first-page":"1546","article-title":"Simultaneous clustering and ensemble","author":"tao","year":"2017","journal-title":"Proc 31st AAAI Conf Artif Intell"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983745"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/1460797.1460800"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1138"},{"key":"ref37","first-page":"665","article-title":"From comparing clusterings to combining clusterings","author":"lu","year":"2008","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972740.35"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2007.98"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2003.1250937"},{"key":"ref28","first-page":"1","article-title":"Probabilistic consensus clustering using evidence accumulation","volume":"98","author":"lourenco","year":"2013","journal-title":"Mach Learn"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.113"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015414"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2619088"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.12056"},{"key":"ref20","first-page":"1359","article-title":"On integrated clustering and outlier detection","author":"ott","year":"2014","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref22","first-page":"1772","article-title":"Semi-crowdsourced clustering: Generalizing crowd labeling by robust distance metric learning","author":"yi","year":"2012","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2011.261"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-017-9742-x"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.57"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2650229"},{"key":"ref25","first-page":"583","article-title":"Cluster ensembles — a knowledge reuse framework for combining partitions","volume":"3","author":"strehl","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref50","first-page":"1705","article-title":"Clustering with bregman divergences","volume":"6","author":"banerjee","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974010.105"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557115"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974010.86"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2316512"},{"key":"ref52","first-page":"1799","article-title":"A theoretic framework of k-means-based consensus clustering","author":"wu","year":"2013","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/335191.335388"},{"key":"ref40","first-page":"1","article-title":"Infinite ensemble clustering","author":"liu","year":"2017","journal-title":"Data Mining Knowl Discovery"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01307-2_84"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401946"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339669"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.99"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974973.55"},{"key":"ref17","first-page":"2891","article-title":"Robust k-means: A theoretical revisit","author":"georgogiannis","year":"2016","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref18","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","author":"ester","year":"1996","journal-title":"Proc ACM SIGKDD Int Conf Knowl Discovery Data Mining"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972832.21"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/2740070.2626334"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/1454008.1454048"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143880"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273523"},{"key":"ref8","first-page":"2189","article-title":"Sparse subspace clustering by learning approximation 0 codes","author":"li","year":"2017","journal-title":"Proc 31st AAAI Conf Artif Intell"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783287"},{"key":"ref7","first-page":"663","article-title":"Robust subspace segmentation by low-rank representation","author":"liu","year":"2010","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/298"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59050-9_12"},{"key":"ref45","first-page":"4390","article-title":"Deep one-class classification","author":"ruff","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref48","article-title":"Anomaly detection with generative adversarial networks for multivariate time series","author":"li","year":"2018","journal-title":"arXiv 1809 04758"},{"key":"ref47","article-title":"Efficient gan-based anomaly detection","author":"zenati","year":"2018","journal-title":"arXiv preprint arXiv 1802 06360"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-47887-6_53"},{"key":"ref41","article-title":"Consensus clustering: An embedding perspective, extension and beyond","author":"liu","year":"2019","journal-title":"arXiv preprint arXiv 1906 00120"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2016.7840665"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.2298\/CSIS0501103H"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/69\/9427778\/8906162-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/9427778\/08906162.pdf?arnumber=8906162","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T10:50:53Z","timestamp":1652179853000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8906162\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,1]]},"references-count":55,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2019.2954317","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,1]]}}}