{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T15:41:15Z","timestamp":1774539675604,"version":"3.50.1"},"reference-count":23,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2015,6,1]],"date-time":"2015-06-01T00:00:00Z","timestamp":1433116800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Ind. Inf."],"published-print":{"date-parts":[[2015,6]]},"DOI":"10.1109\/tii.2015.2411226","type":"journal-article","created":{"date-parts":[[2015,3,9]],"date-time":"2015-03-09T18:53:27Z","timestamp":1425927207000},"page":"583-590","source":"Crossref","is-referenced-by-count":67,"title":["Efficient Motif Discovery for Large-Scale Time Series in Healthcare"],"prefix":"10.1109","volume":"11","author":[{"given":"Bo","family":"Liu","sequence":"first","affiliation":[]},{"given":"Jianqiang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Cheng","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Tan","sequence":"additional","affiliation":[]},{"given":"Qiang","family":"Chen","sequence":"additional","affiliation":[]},{"given":"MengChu","family":"Zhou","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","first-page":"53","article-title":"Finding motifs in time series","author":"lonardi","year":"0","journal-title":"Proc 8th ACM SIGKDD Int Conf Knowl Discovery Data Mining"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956808"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-005-5829-2"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2008.03.022"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/882085.882086"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1089\/10665270252935430"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/1327452.1327492"},{"key":"ref17","year":"2015","journal-title":"Mahout"},{"key":"ref18","first-page":"38","article-title":"Hadoop-ML: An infrastructure for the rapid implementation of parallel reusable analytics","author":"ghoting","year":"0","journal-title":"Proc Large-Scale Mach Learn Parall Massive Data Sets Workshop (NIPS&#x2019;09)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2009.34"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972795.41"},{"key":"ref3","author":"lorica","year":"2013","journal-title":"How Twitter Monitors Millions of Time-Series"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1281192.1281282"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/11430919_41","article-title":"Locating motifs in time-series data","volume":"3518","author":"liu","year":"2005","journal-title":"Advances in Knowledge Discovery and Data Mining"},{"key":"ref8","year":"2015","journal-title":"Apache"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956808"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1109\/TII.2014.2308433","article-title":"An efficient non-negative matrix-factorization-based approach to collaborative filtering for recommender systems","volume":"10","author":"luo","year":"2014","journal-title":"IEEE Trans Ind Informat"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2014.2302638"},{"key":"ref9","author":"keogh","year":"2011","journal-title":"The UCR Time Series Classification\/Clustering Homepage"},{"key":"ref20","first-page":"281","article-title":"Map-reduce for machine learning on multicore","volume":"19","author":"chu","year":"2007","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/PL00011669"},{"key":"ref21","article-title":"A scalable data science workflow approach for big data Bayesian network learning","author":"wang","year":"0","journal-title":"Proc Int Symp Big Data Comput"},{"key":"ref23","first-page":"668","article-title":"Fast Shapelets: A scalable algorithm for discovering time series Shapelets","author":"keogh","year":"0","journal-title":"Proc SDM"}],"container-title":["IEEE Transactions on Industrial Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9424\/7116638\/07056438.pdf?arnumber=7056438","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T16:44:56Z","timestamp":1642005896000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7056438\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,6]]},"references-count":23,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tii.2015.2411226","relation":{},"ISSN":["1551-3203","1941-0050"],"issn-type":[{"value":"1551-3203","type":"print"},{"value":"1941-0050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,6]]}}}