{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T07:44:30Z","timestamp":1759563870140,"version":"3.37.3"},"reference-count":58,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001858","name":"Vinnova, Project: Predictive Maintenance using Advanced Cluster Analysis","doi-asserted-by":"publisher","award":["2019-00789"],"award-info":[{"award-number":["2019-00789"]}],"id":[{"id":"10.13039\/501100001858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3096387","type":"journal-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T20:34:53Z","timestamp":1626122093000},"page":"100063-100080","source":"Crossref","is-referenced-by-count":4,"title":["Multi-Machine Gaussian Topic Modeling for Predictive Maintenance"],"prefix":"10.1109","volume":"9","author":[{"given":"Alexander","family":"Karlsson","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ebru Turanoglu","family":"Bekar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anders","family":"Skoogh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"403","article-title":"Fleet PHM for critical systems: Bi-level deep learning approach for fault detection","volume":"4","author":"michau","year":"2018","journal-title":"Proc Eur Conf PHM Soc"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-05645-2"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s12206-018-0201-1"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"article-title":"Fault detection in a network of similar machines using clustering approach","year":"2012","author":"lapira","key":"ref31"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.5220\/0007830700400050"},{"article-title":"Cyber-physical system augmented prognostics and health management for fleet-based systems","year":"2018","author":"liu","key":"ref37"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2017.02.003"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2013.06.004"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-55852-3_2"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1214\/088342305000000016"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/331499.331504"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s40684-018-0057-y"},{"article-title":"Driving unconventional growth through the industrial Internet of Things","year":"2015","author":"daugherty","key":"ref2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.140"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2523813"},{"journal-title":"Bayesian Data Analysis","year":"2004","author":"gelman","key":"ref22"},{"journal-title":"Bayesian Data Analysis","year":"2004","author":"gelman","key":"ref21"},{"key":"ref24","first-page":"1593","article-title":"The No-U-Turn sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo","volume":"15","author":"homan","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2019.106585"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/app8060916"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3304079.3310286"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiotec.2020.12.002"},{"key":"ref51","first-page":"1","article-title":"Fleet-wide diagnostic and prognostic assessment","author":"voisin","year":"2013","journal-title":"Proc Annu Conf Prognostics Health Manage Soc"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s12599-019-00596-1"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1080\/00949655.2015.1015129"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835940"},{"key":"ref55","first-page":"581","article-title":"Deep learning approach to multiple features sequence analysis in predictive maintenance","author":"yuan","year":"2017","journal-title":"Proc Int Workshop Adv Manuf Autom"},{"key":"ref54","first-page":"648","article-title":"Dirichlet process based evolutionary clustering","author":"xu","year":"2008","journal-title":"Proc 8th IEEE Int Conf Data Mining"},{"key":"ref53","first-page":"789","article-title":"Hierarchical probabilistic models for group anomaly detection","author":"xiong","year":"2011","journal-title":"Proc 14th Int Conf Artif Intell Statist"},{"key":"ref52","first-page":"3","article-title":"An overview of useful data and analyzing techniques for improved multivariate diagnostics and prognostics in condition-based maintenance","author":"wagner","year":"2016","journal-title":"Proc Annu Conf Prognostics Health Manage Soc"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.11.011"},{"key":"ref11","first-page":"551","article-title":"Automated scalable Bayesian inference via Hilbert coresets","volume":"20","author":"campbell","year":"2019","journal-title":"J Mach Learn Res"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2019.03.018"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v076.i01"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2019.106024"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/1150402.1150467"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-99707-0_39"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1016\/j.promfg.2017.07.091","article-title":"Machine learning-based CPS for clustering high throughput machining cycle conditions","volume":"10","author":"diaz-rozo","year":"2017","journal-title":"Procedia Manuf"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2840129"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2018.10.006"},{"year":"2020","author":"azzalini","key":"ref4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCT.2018.8356831"},{"journal-title":"Identifying Bayesian Mixture Models","year":"2017","author":"betancourt","key":"ref6"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176349933"},{"key":"ref8","first-page":"993","article-title":"Latent Dirichlet allocation","volume":"3","author":"blei","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1285773"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1198\/016214506000000302"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2019.107547"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2014.2349359"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9868.00265"},{"key":"ref48","first-page":"1385","article-title":"Sharing clusters among related groups: Hierarchical Dirichlet processes","volume":"17","author":"teh","year":"2005","journal-title":"Advances in neural information processing systems"},{"journal-title":"Stan User&#x2019;s Guide","year":"0","key":"ref47"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9868.00095"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-02203-7_13"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1177\/0954405415601640"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CTS.2013.6567202"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09481148.pdf?arnumber=9481148","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T22:33:01Z","timestamp":1643409181000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9481148\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":58,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3096387","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2021]]}}}