{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T21:32:37Z","timestamp":1773437557573,"version":"3.50.1"},"reference-count":59,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN 262151"],"award-info":[{"award-number":["RGPIN 262151"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Smart Grid"],"published-print":{"date-parts":[[2019,7]]},"DOI":"10.1109\/tsg.2018.2865702","type":"journal-article","created":{"date-parts":[[2018,8,15]],"date-time":"2018-08-15T18:34:35Z","timestamp":1534358075000},"page":"4615-4627","source":"Crossref","is-referenced-by-count":92,"title":["Residential Household Non-Intrusive Load Monitoring via Graph-Based Multi-Label Semi-Supervised Learning"],"prefix":"10.1109","volume":"10","author":[{"given":"Ding","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4225-2770","authenticated-orcid":false,"given":"Scott","family":"Dick","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9780262033589.001.0001"},{"key":"ref38","article-title":"Semi-supervised learning","author":"zhou","year":"2013","journal-title":"Academic Press Library in Signal Processing"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/NAFIPS-WConSC.2015.7284144"},{"key":"ref32","article-title":"The effectiveness of feedback on energy consumption: A review for DEFRA of the literature on metering, billing and direct displays","author":"darby","year":"2006"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2013.2284760"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2015.2494592"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.2200\/S00590ED1V01Y201408AIM029"},{"key":"ref36","first-page":"1","volume":"3","author":"zhu","year":"2009","journal-title":"Introduction to Semi-Supervised Learning"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2008.11.009"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZ-IEEE.2017.8015650"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2014.07.010"},{"key":"ref27","first-page":"1472","article-title":"Approximate inference in additive factorial HMMs with application to energy disaggregation","author":"kolter","year":"2012","journal-title":"Proc Artif Intell Stat"},{"key":"ref29","first-page":"356","article-title":"Non-intrusive load monitoring using prior models of general appliance types","author":"parson","year":"2012","journal-title":"Proc 26th Conf Artif Intell (AAAI)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/PROC.1985.13315"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2012.2203341"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3934\/energy.2016.1.1"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1111\/j.1530-9290.2010.00280.x"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRD.2005.852370"},{"key":"ref24","author":"haykin","year":"2009","journal-title":"Neural Networks and Learning Machines"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2016.7727545"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972818.64"},{"key":"ref25","article-title":"A survey on non-intrusive load monitoring methodies and techniques for energy disaggregation problem","author":"faustine","year":"2017","journal-title":"arXiv preprint arXiv 1703 06870"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/EPEC.2013.6802949"},{"key":"ref51","first-page":"366","volume":"898","author":"takens","year":"1981","journal-title":"Detecting strange attractors in turbulence"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/2602044.2602051"},{"key":"ref58","first-page":"6","article-title":"Unsupervised adaptive event detection for building-level energy disaggregation","author":"barsim","year":"2014","journal-title":"proceedings of Power and Energy Student Summt (PESS)"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/EEEIC.2015.7165334"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/FSKD.2012.6234347"},{"key":"ref55","article-title":"A literature survey on algorithms for multi-label learning","author":"sorower","year":"2010"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.39"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/EPEC.2009.5420779"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511755798"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/5.192069"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2016.2598872"},{"key":"ref40","first-page":"96","article-title":"Efficient non-parametric function induction in semi-supervised learning","author":"delalleau","year":"2005","journal-title":"Proc 10th Int Workshop Artif Intell Stat"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2016.2584581"},{"key":"ref13","author":"haykin","year":"2000","journal-title":"Unsupervised Adaptive Filtering Vol I Blind Source Separation"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2012.6170051"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2015.03.021"},{"key":"ref16","first-page":"912","article-title":"Semi-supervised learning using Gaussian fields and harmonic functions","author":"zhu","year":"2003","journal-title":"Proc 20th Int Conf Mach Learn (ICML)"},{"key":"ref17","first-page":"321","article-title":"Learning with local and global consistency","author":"zhou","year":"2004","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/s121216838"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRD.2009.2033799"},{"key":"ref4","year":"2012","journal-title":"Electricity Explained - Use of Electricity"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2012.2195686"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2010.2089069"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2011.2114678"},{"key":"ref8","article-title":"Residential load control and metering equipment: Costs and capabilities","author":"stickels","year":"1987"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2008.2004732"},{"key":"ref49","first-page":"112","article-title":"Smart*: An open data set and tools for enabling research in sustainable homes","author":"barker","year":"2012","journal-title":"Proc SustKDD"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2228343"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2006.12.019"},{"key":"ref45","first-page":"195","article-title":"Loopy belief propagation for bipartite maximum weight b-matching","author":"huang","year":"2007","journal-title":"Proc Int Conf Artif Intell Stat"},{"key":"ref48","first-page":"1","article-title":"BLUED: A fully labeled public dataset for event-based non-intrusive load monitoring research","author":"anderson","year":"2012","journal-title":"Proc 2nd Workshop Data Min Appl Sustain (SustKDD)"},{"key":"ref47","first-page":"59","article-title":"REDD: A public data set for energy disaggregation research","volume":"25","author":"kolter","year":"2011","journal-title":"Proc Workshop Data Min Appl Sustain (SIGKDD)"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2016.2557460"},{"key":"ref41","first-page":"2399","article-title":"Manifold regularization: A geometric framework for learning from labeled and unlabeled examples","volume":"7","author":"belkin","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553432"},{"key":"ref43","first-page":"771","article-title":"Semi-supervised learning using greedy max-cut","volume":"14","author":"wang","year":"2013","journal-title":"J Mach Learn Res"}],"container-title":["IEEE Transactions on Smart Grid"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5165411\/8741221\/08437176.pdf?arnumber=8437176","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T21:10:21Z","timestamp":1657746621000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8437176\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":59,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tsg.2018.2865702","relation":{},"ISSN":["1949-3053","1949-3061"],"issn-type":[{"value":"1949-3053","type":"print"},{"value":"1949-3061","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7]]}}}