{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T17:51:26Z","timestamp":1710957086522},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2012,8,9]],"date-time":"2012-08-09T00:00:00Z","timestamp":1344470400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2013,10]]},"DOI":"10.1007\/s00521-012-1101-4","type":"journal-article","created":{"date-parts":[[2012,8,8]],"date-time":"2012-08-08T03:03:01Z","timestamp":1344394981000},"page":"1503-1512","source":"Crossref","is-referenced-by-count":11,"title":["Robust and smart spectral clustering from normalized cut"],"prefix":"10.1007","volume":"23","author":[{"given":"Wanzeng","family":"Kong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sanqing","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhai","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guojun","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,8,9]]},"reference":[{"issue":"3","key":"1101_CR1","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1145\/331499.331504","volume":"31","author":"AK Jain","year":"1999","unstructured":"Jain AK, Murty MN, Flynn PJ (1999) Data clustering: a review. ACM Comput Surv 31(3):264\u2013323","journal-title":"ACM Comput Surv"},{"key":"1101_CR2","volume-title":"Pattern classification","author":"RO Duda","year":"2000","unstructured":"Duda RO, Hart PE, Stork DG (2000) Pattern classification, 2nd edn. Wiley, New York","edition":"2"},{"issue":"4","key":"1101_CR3","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1007\/s11222-007-9033-z","volume":"17","author":"U Luxburg","year":"2007","unstructured":"Luxburg U (2007) A tutorial on spectral clustering. Stat Comput 17(4):395\u2013416","journal-title":"Stat Comput"},{"issue":"1","key":"1101_CR4","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.patcog.2007.05.018","volume":"41","author":"M Filipponea","year":"2008","unstructured":"Filipponea M, Camastrab F, Masullia F, Rovetta S (2008) A survey of kernel and spectral methods for clustering. Pattern Recognit 41(1):176\u2013190","journal-title":"Pattern Recognit"},{"key":"1101_CR5","unstructured":"Nga Y, Jordan MI, Weiss Y(2002) On spectral clustering: analysis and an algorithm. Proceedings of the 14th advances in neural information processing systems (NIPS). MIT Press, Cambridge, vol. 200, pp 849\u2013856"},{"key":"1101_CR6","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.ejor.2010.08.012","volume":"211","author":"MCV Nascimento","year":"2011","unstructured":"Nascimento MCV, de Carvalho ACPLF (2011) Spectral methods for graph clustering\u2014a survey. Eur J Oper Res 211:221\u2013231","journal-title":"Eur J Oper Res"},{"key":"1101_CR7","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.neucom.2011.09.002","volume":"77","author":"W Chen","year":"2012","unstructured":"Chen W, Feng G (2012) Spectral clustering: a semi-supervised approach. Neurocomputing 77:229\u2013242","journal-title":"Neurocomputing"},{"key":"1101_CR8","doi-asserted-by":"crossref","first-page":"1924","DOI":"10.1016\/j.patcog.2007.09.009","volume":"41","author":"U Ozertem","year":"2008","unstructured":"Ozertem U, Erdogmus D, Jenssen R (2008) Mean shift spectral clustering. Pattern Recognit 41:1924\u20131938","journal-title":"Pattern Recognit"},{"issue":"5","key":"1101_CR9","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/j.knosys.2011.01.009","volume":"24","author":"P Yang","year":"2011","unstructured":"Yang P, Zhu Q, Huang B (2011) Spectral clustering with density sensitive similarity function. Knowl Based Syst 24(5):621\u2013628","journal-title":"Knowl Based Syst"},{"issue":"1","key":"1101_CR10","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.patcog.2007.04.010","volume":"41","author":"H Chang","year":"2008","unstructured":"Chang H, Yeung DH (2008) Robust path-based spectral clustering. Pattern Recognit 41(1):191\u2013203","journal-title":"Pattern Recognit"},{"key":"1101_CR11","first-page":"1601","volume":"17","author":"ZM Lihi","year":"2005","unstructured":"Lihi ZM, Pietro P (2005) Self-tuning spectral clustering. Adv Neural Inform Process Syst 17:1601\u20131608","journal-title":"Adv Neural Inform Process Syst"},{"issue":"2","key":"1101_CR12","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/j.patrec.2010.09.014","volume":"32","author":"X Zhang","year":"2011","unstructured":"Zhang X, Li J, Yu H (2011) Local density adaptive similarity measurement for spectral clustering. Pattern Recognit Lett 32(2):352\u2013358","journal-title":"Pattern Recognit Lett"},{"issue":"8","key":"1101_CR13","first-page":"1980","volume":"38","author":"W Kong","year":"2010","unstructured":"Kong W, Sun Z, Yang C et al (2010) Automatic spectral clustering based on eigengap and orthogonal eigenvector. Acta Electronica Sinica 38(8):1980\u20131985","journal-title":"Acta Electronica Sinica"},{"key":"1101_CR14","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1016\/j.neucom.2010.12.008","volume":"74","author":"N Rebagliati","year":"2011","unstructured":"Rebagliati N, Verri A (2011) Spectral clustering with more than K eigenvectors. Neurocomputing 74:1391\u20131401","journal-title":"Neurocomputing"},{"issue":"11","key":"1101_CR15","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1109\/34.244673","volume":"15","author":"Z Wu","year":"1993","unstructured":"Wu Z, Leahy R (1993) An optimal graph theoretic approach to data clustering: theory and its application to image segmentation. IEEE Trans Pattern Anal Mach Intell 15(11):1101\u20131113","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1101_CR16","unstructured":"Meila M, Xu L (2004) Multiway cuts and spectral clustering. Technical Report, Department of Statistics, University of Washington, Washington"},{"issue":"2","key":"1101_CR17","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1109\/TPAMI.2004.1262179","volume":"26","author":"SX Yu","year":"2004","unstructured":"Yu SX, Shi J (2004) Segmentation given partial grouping constraints. IEEE Trans Pattern Anal Mach Intell 26(2):173\u2013183","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"9","key":"1101_CR18","doi-asserted-by":"crossref","first-page":"1074","DOI":"10.1109\/43.159993","volume":"11","author":"L Hagen","year":"1992","unstructured":"Hagen L, Kahng AB (1992) New spectral methods for ratio cut partitioning and clustering. IEEE Trans Comput Aided Des 11(9):1074\u20131085","journal-title":"IEEE Trans Comput Aided Des"},{"key":"1101_CR19","doi-asserted-by":"crossref","unstructured":"Ding C, He X, Zha H, Gu M, Simon H (2001) A min\u2013max cut algorithm for graph partitioning and data clustering. In: Proceedings of the IEEE international conference on data mining, pp 107\u2013114","DOI":"10.1109\/ICDM.2001.989507"},{"key":"1101_CR20","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.knosys.2011.11.010","volume":"28","author":"W Chen","year":"2012","unstructured":"Chen W, Feng G (2012) Spectral clustering with discriminant cuts. Knowl Based Syst 28:27\u201337","journal-title":"Knowl Based Syst"},{"key":"1101_CR21","doi-asserted-by":"crossref","unstructured":"Dhillon IS, Guan Y, Kulis B (2004) Kernel k-means: spectral clustering and normalized cuts. In: International Conference on KDD, pp 551\u2013556","DOI":"10.1145\/1014052.1014118"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-1101-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-012-1101-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-1101-4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T16:19:17Z","timestamp":1562084357000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-012-1101-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,8,9]]},"references-count":21,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2013,10]]}},"alternative-id":["1101"],"URL":"https:\/\/doi.org\/10.1007\/s00521-012-1101-4","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,8,9]]}}}