{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T15:14:35Z","timestamp":1777734875238,"version":"3.51.4"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2016,9,26]],"date-time":"2016-09-26T00:00:00Z","timestamp":1474848000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61174114"],"award-info":[{"award-number":["61174114"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["U1509203"],"award-info":[{"award-number":["U1509203"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Research Fund for the Doctoral Program of Higher Education in China","award":["20120101130016"],"award-info":[{"award-number":["20120101130016"]}]},{"name":"the Zhejiang Provincial Science and Technology Planning Projects of China","award":["2014C31019"],"award-info":[{"award-number":["2014C31019"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2017,6]]},"DOI":"10.1007\/s11063-016-9555-5","type":"journal-article","created":{"date-parts":[[2016,9,25]],"date-time":"2016-09-25T23:18:09Z","timestamp":1474845489000},"page":"925-937","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["A Novel Similarity Measure Model for Multivariate Time Series Based on LMNN and DTW"],"prefix":"10.1007","volume":"45","author":[{"given":"Jingyi","family":"Shen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiping","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongyang","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,9,26]]},"reference":[{"key":"9555_CR1","volume-title":"Time series: applications to finance","author":"NH Chan","year":"2002","unstructured":"Chan NH (2002) Time series: applications to finance. Wiley, Hoboken"},{"issue":"1","key":"9555_CR2","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.artmed.2008.11.007","volume":"45","author":"P Tormene","year":"2008","unstructured":"Tormene P, Giorgino T, Quaglini S, Stefanelli M (2008) Matching incomplete time series with dynamic time warping: an algorithm and an application to post-stroke rehabilitation. Artif Intell Med 45(1):11\u201334","journal-title":"Artif Intell Med"},{"issue":"8","key":"9555_CR3","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1002\/cem.945","volume":"19","author":"DE Seborg","year":"2005","unstructured":"Seborg DE, Singhal A (2005) Clustering multivariate time-series data. J Chemom 19(8):427\u2013438","journal-title":"J Chemom"},{"issue":"6","key":"9555_CR4","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1093\/bioinformatics\/17.6.495","volume":"17","author":"J Aach","year":"2001","unstructured":"Aach J, Church GM (2001) Aligning gene expression time series with time warping algorithms. Bioinformatics 17(6):495\u2013508","journal-title":"Bioinformatics"},{"issue":"1","key":"9555_CR5","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"TM Cover","year":"1967","unstructured":"Cover TM, Hart PE (1967) Nearest neighbor pattern classification. IEEE Trans Inf Theory 13(1):21\u201327","journal-title":"IEEE Trans Inf Theory"},{"issue":"1","key":"9555_CR6","doi-asserted-by":"crossref","first-page":"100","DOI":"10.2307\/2346830","volume":"28","author":"JA Hartigan","year":"1979","unstructured":"Hartigan JA, Wong MA (1979) A K-means clustering algorithm. Appl Stat 28(1):100\u2013108","journal-title":"Appl Stat"},{"issue":"3","key":"9555_CR7","first-page":"1303","volume":"1","author":"MM Adankon","year":"2002","unstructured":"Adankon MM, Cheriet M (2002) Support vector machine. Comput Sci 1(3):1303\u20131308","journal-title":"Comput Sci"},{"key":"9555_CR8","unstructured":"Berndt DJ, Clifford J (1994) Using dynamic time warping to find patterns in time series. In: Advances in knowledge discovery in databases papers from the Aaai workshop"},{"key":"9555_CR9","series-title":"Lecture notes in computer science","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1007\/978-3-642-02982-0_25","volume-title":"Robust adaptable video copy detection","author":"I Assent","year":"2009","unstructured":"Assent I, Kremer H (2009) Robust adaptable video copy detection., Lecture notes in computer scienceSpringer, New York, pp 380\u2013385"},{"key":"9555_CR10","unstructured":"Gavrila DM, Davis LS (1995) 3-D model-based tracking of human upper body movement: a multi-viewapproach. In: IEEE, pp 253\u2013258"},{"key":"9555_CR11","unstructured":"Schmill MD, Oates T, Cohen PR, Schmill MD (2000) Learned models for continuous planning. In: Proceedings of uncertainty the seventh international workshop on artificial intelligence & statistics, pp. 278\u2013282"},{"key":"9555_CR12","doi-asserted-by":"crossref","unstructured":"Keogh EJ, Pazzani MJ (1999) Scaling up dynamic time warping to massive dataset. In: Proceedings of the third european conference on principles of data mining and knowledge discovery, pp 1\u201311","DOI":"10.1007\/978-3-540-48247-5_1"},{"key":"9555_CR13","unstructured":"ten Holt GA, Reinders MJ, Hendriks E (2007) Multi-dimensional dynamic time warping for gesture recognition. In: Thirteenth annual conference of the advanced school for computing and imaging"},{"issue":"11","key":"9555_CR14","doi-asserted-by":"crossref","first-page":"3787","DOI":"10.1016\/j.patcog.2010.06.005","volume":"43","author":"C Orsenigo","year":"2010","unstructured":"Orsenigo C, Vercellis C (2010) Combining discrete SVM and fixed cardinality warping distances for multivariate time series classification. Pattern Recognit 43(11):3787\u20133794","journal-title":"Pattern Recognit"},{"key":"9555_CR15","doi-asserted-by":"crossref","unstructured":"Mei J, Liu M, Wang YF, Gao H (2015) Learning a mahalanobis distance-based dynamic time warping measure for multivariate time series classification. IEEE Trans Cybern, p 1","DOI":"10.1109\/TCYB.2015.2426723"},{"key":"9555_CR16","volume-title":"Distance metric learning: a comprehensive survey","author":"L Yang","year":"2006","unstructured":"Yang L (2006) Distance metric learning: a comprehensive survey. Michigan State Universiy, East Lansing"},{"key":"9555_CR17","first-page":"505","volume":"15","author":"EP Xing","year":"2002","unstructured":"Xing EP, Ng AY, Jordan MI, Russell S (2002) Distance metric learning, with application to clustering with side-information. Adv Neural Inf Process Syst 15:505\u2013512","journal-title":"Adv Neural Inf Process Syst"},{"key":"9555_CR18","unstructured":"Barhillel BA, Hertz T Shental N, Weinshall D (2003) Learning distance functions using equivalence relations. In: Proceedings of the 20th international conference on machine learning, 2012"},{"issue":"6","key":"9555_CR19","first-page":"513","volume":"83","author":"J Goldberger","year":"2004","unstructured":"Goldberger J, Roweis ST, Hinton GE, Salakhutdinov R (2004) Neighbourhood components analysis. Adv Neural Inf Process Syst 83(6):513\u2013520","journal-title":"Adv Neural Inf Process Syst"},{"issue":"1","key":"9555_CR20","first-page":"207","volume":"10","author":"KQ Weinberger","year":"2009","unstructured":"Weinberger KQ, Saul LK (2009) Distance metric learning for large margin nearest neighbor classification. J Mach Learn Res 10(1):207\u2013244","journal-title":"J Mach Learn Res"},{"issue":"11","key":"9555_CR21","doi-asserted-by":"crossref","first-page":"4920","DOI":"10.1109\/TIP.2014.2359765","volume":"23","author":"J Mei","year":"2014","unstructured":"Mei J, Liu M, Karimi HR, Gao H (2014) LogDet divergence-based metric learning with triplet constraints and its applications. IEEE Trans Image Process A Publ IEEE Signal Process Soc 23(11):4920\u20134931","journal-title":"IEEE Trans Image Process A Publ IEEE Signal Process Soc"},{"key":"9555_CR22","unstructured":"Do H, Kalousis A, Wang J, Woznica A (2012) A metric learning perspective of SVM: on the relation of SVM and LMNN. Eprint arXiv:308-317"},{"key":"9555_CR23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12193-015-0194-3","volume":"9","author":"T Marasovic","year":"2015","unstructured":"Marasovic T, Papic V, Zanchi V (2015) LMNN metric learning and fuzzy nearest neighbour classifier for hand gesture recognition. J Multimodal User Interfaces 9:1\u201311","journal-title":"J Multimodal User Interfaces"},{"key":"9555_CR24","volume-title":"Numerical optimization","author":"J Nocedal","year":"2006","unstructured":"Nocedal J, Wright S (2006) Numerical optimization. Springer, New York"},{"issue":"6","key":"9555_CR25","doi-asserted-by":"crossref","first-page":"409","DOI":"10.6028\/jres.049.044","volume":"49","author":"MR Hestenes","year":"1952","unstructured":"Hestenes MR, Stiefel E (1952) Methods of conjugate gradients for solving Linear systems. J Res Natl Bureau Stand 49(6):409\u2013436","journal-title":"J Res Natl Bureau Stand"},{"key":"9555_CR26","doi-asserted-by":"crossref","unstructured":"Byrd RH, Lu P, Nocedal J, Zhu C (1996) A limited memory algorithm for bound constrained optimization. Office of Scientific & Technical Information Technical Reports","DOI":"10.2172\/204262"},{"key":"9555_CR27","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1007\/BF01589116","volume":"45","author":"DC Liu","year":"1989","unstructured":"Liu DC, Nocedal J (1989) On the limited memory BFGS method for large scale optimization. Math Program 45:503\u2013528","journal-title":"Math Program"},{"issue":"1","key":"9555_CR28","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10107-015-0892-3","volume":"151","author":"SJ Wright","year":"2015","unstructured":"Wright SJ (2015) Coordinate descent algorithms. Math Program 151(1):3\u201334","journal-title":"Math Program"},{"key":"9555_CR29","first-page":"49","volume":"2","author":"PC Mahalanobis","year":"1936","unstructured":"Mahalanobis PC (1936) On the generalized distance in statistics. Proc Natl Inst Sci 2:49\u201355","journal-title":"Proc Natl Inst Sci"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-016-9555-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-016-9555-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-016-9555-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T20:27:58Z","timestamp":1568406478000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-016-9555-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,9,26]]},"references-count":29,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2017,6]]}},"alternative-id":["9555"],"URL":"https:\/\/doi.org\/10.1007\/s11063-016-9555-5","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"value":"1370-4621","type":"print"},{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,9,26]]}}}