{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:41:25Z","timestamp":1740109285500,"version":"3.37.3"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2016,11,28]],"date-time":"2016-11-28T00:00:00Z","timestamp":1480291200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2017,7]]},"DOI":"10.1007\/s10115-016-1008-y","type":"journal-article","created":{"date-parts":[[2016,11,28]],"date-time":"2016-11-28T05:52:15Z","timestamp":1480312335000},"page":"179-219","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["rFILTA: relevant and nonredundant view discovery from collections of clusterings via filtering and ranking"],"prefix":"10.1007","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3780-6510","authenticated-orcid":false,"given":"Yang","family":"Lei","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nguyen Xuan","family":"Vinh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey","family":"Chan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James","family":"Bailey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,11,28]]},"reference":[{"key":"1008_CR1","unstructured":"Azimi J, Fern X (2009) Adaptive cluster ensemble selection. In: IJCAI vol 9, pp 992\u2013997"},{"key":"1008_CR2","unstructured":"Bache K, Lichman M (2013) UCI machine learning repository. URL http:\/\/archive.ics.uci.edu\/ml"},{"key":"1008_CR3","doi-asserted-by":"crossref","unstructured":"Bae E, Bailey J Coala (2006) A novel approach for the extraction of an alternate clustering of high quality and high dissimilarity. In: Sixth international conference on data mining, 2006 (ICDM\u201906). IEEE, pp 53\u201362","DOI":"10.1109\/ICDM.2006.37"},{"key":"1008_CR4","volume-title":"Data clustering: algorithms and applications","author":"J Bailey","year":"2013","unstructured":"Bailey J (2013) Alternative clustering analysis: a review. In: Aggarwal C, Reddy C (eds) Data clustering: algorithms and applications. CRC Press, Boca Raton"},{"key":"1008_CR5","doi-asserted-by":"crossref","unstructured":"Caruana R, Elhaway M, Nguyen N, Smith C (2006) Meta clustering. In: Proceedings of ICDM, pp 107\u2013118","DOI":"10.1109\/ICDM.2006.103"},{"key":"1008_CR6","unstructured":"Cui Y, Fern XZ, Dy JG (2007) Multi-view clustering via orthogonalization. In: Proceedings of ICDM, pp 133\u2013142"},{"key":"1008_CR7","doi-asserted-by":"crossref","unstructured":"Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society Conference on computer vision and pattern recognition, 2005 (CVPR\u20192005) IEEE, vol 1, pp 886\u2013893","DOI":"10.1109\/CVPR.2005.177"},{"key":"1008_CR8","doi-asserted-by":"crossref","unstructured":"Dang XH, Bailey J (2010) A hierarchical information theoretic technique for the discovery of non linear alternative clusterings. In: Proceedings of the of (KDD\u201910), pp 573\u2013582","DOI":"10.1145\/1835804.1835878"},{"issue":"3","key":"1008_CR9","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1007\/s10618-013-0314-1","volume":"28","author":"XH Dang","year":"2014","unstructured":"Dang XH, Bailey J (2014) Generating multiple alternative clusterings via globally optimal subspaces. Data Min Knowl Discov 28(3):569\u2013592","journal-title":"Data Min Knowl Discov"},{"issue":"1\u20132","key":"1008_CR10","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s10994-013-5338-7","volume":"98","author":"XH Dang","year":"2015","unstructured":"Dang XH, Bailey J (2015) A framework to uncover multiple alternative clusterings. Mach Learn 98(1\u20132):7\u201330","journal-title":"Mach Learn"},{"key":"1008_CR11","doi-asserted-by":"crossref","unstructured":"Davidson I, Qi Z (2008) Finding alternative clusterings using constraints. In: Proceedings of ICDM, pp 773\u2013778","DOI":"10.1109\/ICDM.2008.141"},{"key":"1008_CR12","unstructured":"Faivishevsky L, Goldberger J (2010) Nonparametric information theoretic clustering algorithm. In: Proceedings of ICML, pp 351\u2013358"},{"issue":"3","key":"1008_CR13","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1002\/sam.10008","volume":"1","author":"XZ Fern","year":"2008","unstructured":"Fern XZ, Lin W (2008) Cluster ensemble selection. Stat Anal Data Min 1(3):128\u2013141","journal-title":"Stat Anal Data Min"},{"issue":"1","key":"1008_CR14","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1145\/1217299.1217303","volume":"1","author":"A Gionis","year":"2007","unstructured":"Gionis A, Mannila H, Tsaparas P (2007) Clustering aggregation. ACM Trans Knowl Discov Data (TKDD) 1(1):4","journal-title":"ACM Trans Knowl Discov Data (TKDD)"},{"key":"1008_CR15","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/0304-3975(85)90224-5","volume":"38","author":"TF Gonzalez","year":"1985","unstructured":"Gonzalez TF (1985) Clustering to minimize the maximum intercluster distance. Theor Comput Sci 38:293\u2013306","journal-title":"Theor Comput Sci"},{"issue":"1\u20132","key":"1008_CR16","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s10994-013-5395-y","volume":"98","author":"F Gullo","year":"2015","unstructured":"Gullo F, Domeniconi C, Tagarelli A (2015) Metacluster-based projective clustering ensembles. Mach Learn 98(1\u20132):181\u2013216","journal-title":"Mach Learn"},{"issue":"3","key":"1008_CR17","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.inffus.2005.01.008","volume":"7","author":"ST Hadjitodorov","year":"2006","unstructured":"Hadjitodorov ST, Kuncheva LI, Todorova LP (2006) Moderate diversity for better cluster ensembles. Inf Fusion 7(3):264\u2013275","journal-title":"Inf Fusion"},{"issue":"5","key":"1008_CR18","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1109\/TKDE.2011.33","volume":"24","author":"TC Havens","year":"2012","unstructured":"Havens TC, Bezdek JC (2012) An efficient formulation of the improved visual assessment of cluster tendency (iVAT) algorithm. IEEE Trans Knowl Data Eng 24(5):813\u2013822","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"5","key":"1008_CR19","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1002\/int.20344","volume":"24","author":"TC Havens","year":"2009","unstructured":"Havens TC, Bezdek JC, Keller JM, Popescu M (2009) Clustering in ordered dissimilarity data. Int J Int Syst 24(5):504\u2013528","journal-title":"Int J Int Syst"},{"issue":"2","key":"1008_CR20","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/s10618-012-0288-4","volume":"27","author":"MS Hossain","year":"2013","unstructured":"Hossain MS, Ramakrishnan N, Davidson I, Watson LT (2013) How to \u201calternatize\u201d a clustering algorithm. Data Min Knowl Discov 27(2):193\u2013224","journal-title":"Data Min Knowl Discov"},{"key":"1008_CR21","volume-title":"Algorithms for clustering data","author":"AK Jain","year":"1988","unstructured":"Jain AK, Dubes RC (1988) Algorithms for clustering data. Prentice-Hall, Englewood Cliffs"},{"issue":"3","key":"1008_CR22","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1002\/sam.10007","volume":"1","author":"P Jain","year":"2008","unstructured":"Jain P, Meka R, Dhillon IS (2008) Simultaneous unsupervised learning of disparate clusterings. Stat Anal Data Min: ASA Data Sci J 1(3):195\u2013210","journal-title":"Stat Anal Data Min: ASA Data Sci J"},{"issue":"2","key":"1008_CR23","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1007\/s10115-015-0851-6","volume":"47","author":"PA Jaskowiak","year":"2016","unstructured":"Jaskowiak PA, Moulavi D, Furtado AC, Campello RJ, Zimek A, Sander J (2016) On strategies for building effective ensembles of relative clustering validity criteria. Knowl Inf Syst 47(2):329\u2013354","journal-title":"Knowl Inf Syst"},{"key":"1008_CR24","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1007\/978-3-662-44851-9_10","volume-title":"Machine learning and knowledge discovery in databases","author":"Y Lei","year":"2014","unstructured":"Lei Y, Vinh NX, Chan J, Bailey J (2014) Filta Better view discovery from collections of clusterings via filtering. Machine learning and knowledge discovery in databases. Springer, Berlin, pp 145\u2013160"},{"key":"1008_CR25","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511809071","volume-title":"Introduction to information retrieval","author":"CD Manning","year":"2008","unstructured":"Manning CD, Raghavan P, Sch\u00fctze H (2008) Introduction to information retrieval, vol 1. Cambridge University Press, Cambridge"},{"issue":"2","key":"1008_CR26","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s10618-012-0290-x","volume":"27","author":"MC Naldi","year":"2013","unstructured":"Naldi MC, Carvalho A, Campello RJ (2013) Cluster ensemble selection based on relative validity indexes. Data Min Knowl Discov 27(2):259\u2013289","journal-title":"Data Min Knowl Discov"},{"key":"1008_CR27","doi-asserted-by":"crossref","unstructured":"Nguyen N, Caruana R (2007) Consensus clusterings. In: Seventh IEEE international conference on data mining (ICDM\u20192007). IEEE, pp 607\u2013612","DOI":"10.1109\/ICDM.2007.73"},{"issue":"1","key":"1008_CR28","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1109\/TSMCB.2011.2161607","volume":"42","author":"F Nie","year":"2012","unstructured":"Nie F, Xu D, Li X (2012) Initialization independent clustering with actively self-training method. IEEE Trans Syst, Man, Cybern, Part B (Cybern) 42(1):17\u201327","journal-title":"IEEE Trans Syst, Man, Cybern, Part B (Cybern)"},{"key":"1008_CR29","doi-asserted-by":"crossref","unstructured":"Nie F, Wang X, Huang H (2014) Clustering and projected clustering with adaptive neighbors. In: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, pp 977\u2013986","DOI":"10.1145\/2623330.2623726"},{"key":"1008_CR30","doi-asserted-by":"crossref","unstructured":"Nilsback ME, Zisserman A (2006) A visual vocabulary for flower classification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, vol 2, pp 1447\u20131454","DOI":"10.1109\/CVPR.2006.42"},{"issue":"7","key":"1008_CR31","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1109\/TPAMI.2013.180","volume":"36","author":"D Niu","year":"2014","unstructured":"Niu D, Dy JG, Jordan MI (2014) Iterative discovery of multiple alternativeclustering views. IEEE Trans Pattern Anal Mach Intell 36(7):1340\u20131353","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"8","key":"1008_CR32","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","volume":"27","author":"H Peng","year":"2005","unstructured":"Peng H, Long F, Ding C (2005) Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell 27(8):1226\u20131238","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1008_CR33","unstructured":"Phillips JM, Raman P, Venkatasubramanian S (2011) Generating a diverse set of high-quality clusterings. arXiv:1108.0017"},{"issue":"13","key":"1008_CR34","doi-asserted-by":"crossref","first-page":"1607","DOI":"10.1093\/bioinformatics\/btm158","volume":"23","author":"V Pihur","year":"2007","unstructured":"Pihur V, Datta S, Datta S (2007) Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach. Bioinformatics 23(13):1607\u20131615","journal-title":"Bioinformatics"},{"key":"1008_CR35","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"PJ Rousseeuw","year":"1987","unstructured":"Rousseeuw PJ (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20:53\u201365","journal-title":"J Comput Appl Math"},{"issue":"6","key":"1008_CR36","doi-asserted-by":"crossref","first-page":"1156","DOI":"10.1109\/TSMCB.2005.850173","volume":"35","author":"W Sheng","year":"2005","unstructured":"Sheng W, Swift S, Zhang L, Liu X (2005) A weighted sum validity function for clustering with a hybrid niching genetic algorithm. IEEE Trans Syst, Man, Cybern, Part B (Cybern) 35(6):1156\u20131167","journal-title":"IEEE Trans Syst, Man, Cybern, Part B (Cybern)"},{"key":"1008_CR37","first-page":"583","volume":"3","author":"A Strehl","year":"2003","unstructured":"Strehl A, Ghosh J (2003) Cluster ensembles: a knowledge reuse framework for combining multiple partitions. J Mach Learn Res 3:583\u2013617","journal-title":"J Mach Learn Res"},{"issue":"12","key":"1008_CR38","doi-asserted-by":"crossref","first-page":"1866","DOI":"10.1109\/TPAMI.2005.237","volume":"27","author":"A Topchy","year":"2005","unstructured":"Topchy A, Jain AK, Punch W (2005) Clustering ensembles: models of consensus and weak partitions. IEEE Trans Pattern Anal Mach Intell 27(12):1866\u20131881","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1008_CR39","doi-asserted-by":"crossref","unstructured":"Vinh NX, Epps J (2010) minCEntropy: a novel information theoretic approach for the generation of alternative clusterings. In: Proceedings of the ICDM, pp 521\u2013530","DOI":"10.1109\/ICDM.2010.24"},{"key":"1008_CR40","doi-asserted-by":"crossref","unstructured":"Vinh NX, Epps J, Bailey J (2009) Information theoretic measures for clusterings comparison: is a correction for chance necessary? In: Proceedings of ICML. ACM, pp 1073\u20131080","DOI":"10.1145\/1553374.1553511"},{"key":"1008_CR41","doi-asserted-by":"crossref","unstructured":"Wang L, Nguyen UT, Bezdek JC, Leckie CA, Ramamohanarao K (2010) iVAT and aVAT: enhanced visual analysis for cluster tendency assessment. In: Proceedings of PAKDD, pp 16\u201327","DOI":"10.1007\/978-3-642-13657-3_5"},{"issue":"1","key":"1008_CR42","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1002\/sam.10098","volume":"4","author":"H Wang","year":"2011","unstructured":"Wang H, Shan H, Banerjee A (2011) Bayesian cluster ensembles. Stat Anal Data Min 4(1):54\u201370","journal-title":"Stat Anal Data Min"},{"key":"1008_CR43","doi-asserted-by":"crossref","unstructured":"Zhang Y, Li T (2011) Extending consensus clustering to explore multiple clustering views. In: Proceedings of the SDM, pp 920\u2013931","DOI":"10.1137\/1.9781611972818.79"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-016-1008-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-016-1008-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-016-1008-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,15]],"date-time":"2019-09-15T21:04:44Z","timestamp":1568581484000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-016-1008-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11,28]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,7]]}},"alternative-id":["1008"],"URL":"https:\/\/doi.org\/10.1007\/s10115-016-1008-y","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"type":"print","value":"0219-1377"},{"type":"electronic","value":"0219-3116"}],"subject":[],"published":{"date-parts":[[2016,11,28]]}}}