{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:24:56Z","timestamp":1775607896003,"version":"3.50.1"},"reference-count":79,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2018,6,21]],"date-time":"2018-06-21T00:00:00Z","timestamp":1529539200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"published-print":{"date-parts":[[2019,8]]},"DOI":"10.1007\/s10462-018-9642-2","type":"journal-article","created":{"date-parts":[[2018,6,21]],"date-time":"2018-06-21T16:40:28Z","timestamp":1529599228000},"page":"1311-1340","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":80,"title":["Clustering ensemble selection considering quality and diversity"],"prefix":"10.1007","volume":"52","author":[{"given":"Sadr-olah","family":"Abbasi","sequence":"first","affiliation":[]},{"given":"Samad","family":"Nejatian","sequence":"additional","affiliation":[]},{"given":"Hamid","family":"Parvin","sequence":"additional","affiliation":[]},{"given":"Vahideh","family":"Rezaie","sequence":"additional","affiliation":[]},{"given":"Karamolah","family":"Bagherifard","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,6,21]]},"reference":[{"key":"9642_CR1","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.engappai.2014.12.005","volume":"39","author":"E Akbari","year":"2015","unstructured":"Akbari E, Dahlan HM, Ibrahim R, Alizadeh H (2015) Hierarchical cluster ensemble selection. Eng Appl Artif Intell 39:146\u2013156","journal-title":"Eng Appl Artif Intell"},{"key":"9642_CR2","unstructured":"Alizadeh H (2008) Clustering ensemble based on a subset of primary clusters. M.Sc. Dissertation, Iran University of Science and Technology (in Persian)"},{"key":"9642_CR3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-3-642-21332-8_1","volume":"363","author":"H Alizadeh","year":"2011","unstructured":"Alizadeh H, Minaei-Bidgoli B, Parvin H, Moshki M (2011a) An asymmetric criterion for cluster validation, developing concepts in applied intelligence. Stud Comput Intell 363:1\u201314","journal-title":"Stud Comput Intell"},{"key":"9642_CR4","doi-asserted-by":"crossref","unstructured":"Alizadeh H, Minaei-Bidgoli B, Parvin H (2011b) A new criterion for clusters validation. In: Artificial intelligence applications and innovations (AIAI 2011), IFIP, Part I. Springer, Heidelberg, pp 240\u2013246","DOI":"10.1007\/978-3-642-23960-1_14"},{"issue":"3","key":"9642_CR5","doi-asserted-by":"publisher","first-page":"389","DOI":"10.3233\/IDA-140647","volume":"18","author":"H Alizadeh","year":"2014","unstructured":"Alizadeh H, Minaeibidgoli B, Parvin H (2014a) Cluster ensemble selection based on a new cluster stability measure. Intell Data Anal 18(3):389\u2013408","journal-title":"Intell Data Anal"},{"issue":"1","key":"9642_CR6","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1080\/0952813X.2013.813974","volume":"26","author":"H Alizadeh","year":"2014","unstructured":"Alizadeh H, Minaei-Bidgoli B, Parvin H (2014b) To improve the quality of cluster ensembles by selecting a subset of base clusters. J Exp Theor Artif Intell 26(1):127\u2013150","journal-title":"J Exp Theor Artif Intell"},{"issue":"3","key":"9642_CR7","doi-asserted-by":"publisher","first-page":"485","DOI":"10.3233\/IDA-150728","volume":"19","author":"H Alizadeh","year":"2015","unstructured":"Alizadeh H, Yousefnezhad M, Minaei-Bidgoli B (2015) Wisdom of crowds cluster ensemble. Intell Data Anal 19(3):485\u2013503","journal-title":"Intell Data Anal"},{"key":"9642_CR8","doi-asserted-by":"crossref","unstructured":"Ayad H, Kamel MS (2003) Finding natural clusters using multiclusterer combiner based on shared nearest neighbors. In: Proceedings of the fourth international workshop on multiple classifier systems, pp 166\u2013175","DOI":"10.1007\/3-540-44938-8_17"},{"issue":"1","key":"9642_CR9","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1109\/TPAMI.2007.1138","volume":"30","author":"HG Ayad","year":"2008","unstructured":"Ayad HG, Kamel MS (2008) Cumulative voting consensus method for partitions with a variable number of clusters. IEEE Trans Pattern Anal Mach Intell 30(1):160\u2013173","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"5","key":"9642_CR10","doi-asserted-by":"publisher","first-page":"1943","DOI":"10.1016\/j.patcog.2009.11.012","volume":"43","author":"H Ayad","year":"2010","unstructured":"Ayad H, Kamel MS (2010) On voting-based consensus of cluster ensembles. Pattern Recogn 43(5):1943\u20131953","journal-title":"Pattern Recogn"},{"key":"9642_CR11","unstructured":"Azimi J (2008) An informed clustering ensemble. M.Sc. Dissertation, Iran University of Science and Technology (in Persian)"},{"key":"9642_CR12","unstructured":"Azimi J, Fern X (2009) Adaptive cluster ensemble selection. In: IJCAI 2009, pp 992\u2013997"},{"key":"9642_CR13","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1002\/(SICI)1522-2586(200002)11:2<228::AID-JMRI23>3.0.CO;2-Z","volume":"11","author":"R Baumgartner","year":"2000","unstructured":"Baumgartner R, Somorjai R, Summers R, Richter W, Ryner L, Jarmasz M (2000) Resampling as a cluster validation technique in fMRI. J Magn Reson Imaging 11:228\u2013231","journal-title":"J Magn Reson Imaging"},{"key":"9642_CR14","first-page":"6","volume":"7","author":"A Ben-Hur","year":"2002","unstructured":"Ben-Hur A, Elisseeff A, Guyon I (2002) A stability based method for discovering structure in clustered data. Pac Symp Biocomput 7:6\u201317","journal-title":"Pac Symp Biocomput"},{"key":"9642_CR15","doi-asserted-by":"publisher","first-page":"195","DOI":"10.5194\/hess-2-195-1998","volume":"2","author":"T Brandsma","year":"1998","unstructured":"Brandsma T, Buishand TA (1998) Simulation of extreme precipitation in the Rhine basin by nearest-neighbour resampling. Hydrol Earth Syst Sci 2:195\u2013209","journal-title":"Hydrol Earth Syst Sci"},{"issue":"2","key":"9642_CR16","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1207\/s15327906mbr2402_1","volume":"24","author":"J Breckenridge","year":"1989","unstructured":"Breckenridge J (1989) Replicating cluster analysis: method, consistency and validity. Multivar Behav Res 24(2):147\u2013161. https:\/\/doi.org\/10.1207\/s15327906mbr2402_1","journal-title":"Multivar Behav Res"},{"issue":"2","key":"9642_CR17","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1109\/TPAMI.2010.85","volume":"33","author":"IT Christou","year":"2011","unstructured":"Christou IT (2011) Coordination of cluster ensembles via exact methods. IEEE Trans Pattern Anal Mach Intell 33(2):279\u2013293","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9642_CR18","doi-asserted-by":"crossref","unstructured":"Das AK, Sil J (2007) Cluster validation using splitting and merging technique. In: International conference on computational intelligence and multimedia applications, ICCIMA","DOI":"10.1109\/ICCIMA.2007.87"},{"key":"9642_CR19","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1214\/ss\/1063994969","volume":"18","author":"AC Davison","year":"2003","unstructured":"Davison AC, Hinkley DV, Young GA (2003) Recent developments in bootstrap methodology. Stat Sci 18:141\u2013157","journal-title":"Stat Sci"},{"issue":"1","key":"9642_CR20","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/T-AFFC.2010.15","volume":"2","author":"RR Derakhshani","year":"2011","unstructured":"Derakhshani RR (2011) An ensemble method for classifying startle eyeblink modulation from high-speed video records. IEEE Trans Affect Comput 2(1):50\u201363","journal-title":"IEEE Trans Affect Comput"},{"issue":"10","key":"9642_CR21","doi-asserted-by":"publisher","first-page":"1895","DOI":"10.1162\/089976698300017197","volume":"7","author":"TG Dietterich","year":"1998","unstructured":"Dietterich TG (1998) Approximate statistical tests for comparing supervised classification learning algorithms. Neural Comput 7(10):1895\u20131924","journal-title":"Neural Comput"},{"issue":"4","key":"9642_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1460797.1460800","volume":"2","author":"C Domeniconi","year":"2009","unstructured":"Domeniconi C, Al-Razgan M (2009) Weighted cluster ensembles: methods and analysis. ACM Trans Knowl Discov Data (TKDD) 2(4):1\u201342","journal-title":"ACM Trans Knowl Discov Data (TKDD)"},{"key":"9642_CR23","volume-title":"Pattern classification","author":"RO Duda","year":"2001","unstructured":"Duda RO, Hart PE, Stork DG (2001) Pattern classification, 2nd edn. Wiley, New York","edition":"2"},{"key":"9642_CR24","doi-asserted-by":"crossref","unstructured":"Estivill-Castro V, Yang J (2003) Cluster validity using support vector machines. In: DaWaK 2003, LNCS, vol 2737, pp 244\u2013256","DOI":"10.1007\/978-3-540-45228-7_25"},{"key":"9642_CR25","doi-asserted-by":"crossref","unstructured":"Faceli K, Marcilio CP, Souto D (2006) Multi-objective clustering ensemble. In: Proceedings of the sixth international conference on hybrid intelligent systems","DOI":"10.1109\/HIS.2006.264934"},{"key":"9642_CR26","doi-asserted-by":"crossref","unstructured":"Fern XZ, Lin W (2008) Cluster ensemble selection. In: SIAM international conference on data mining","DOI":"10.1137\/1.9781611972788.71"},{"issue":"11","key":"9642_CR27","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.1109\/TPAMI.2003.1240115","volume":"25","author":"B Fischer","year":"2003","unstructured":"Fischer B, Buhmann J (2003) Bagging for path-based clustering. IEEE Trans Pattern Anal Mach Intell 25(11):1411\u20131415","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"9642_CR28","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1016\/j.patcog.2013.08.019","volume":"47","author":"L Franek","year":"2014","unstructured":"Franek L, Jiang X (2014) Ensemble clustering by means of clustering embedding in vector spaces. Pattern Recogn 47(2):833\u2013842","journal-title":"Pattern Recogn"},{"key":"9642_CR29","doi-asserted-by":"crossref","unstructured":"Fred A, Jain AK (2002) Data clustering using evidence accumulation. In: International conference on pattern recognition, ICPR02, Quebec City, pp 276\u2013280","DOI":"10.1109\/ICPR.2002.1047450"},{"issue":"6","key":"9642_CR30","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1109\/TPAMI.2005.113","volume":"27","author":"A Fred","year":"2005","unstructured":"Fred A, Jain AK (2005) Combining multiple clusterings using evidence accumulation. IEEE Trans Pattern Anal Mach Intell 27(6):835\u2013850","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9642_CR31","doi-asserted-by":"crossref","unstructured":"Fred A, Jain AK (2006) Learning pairwise similarity for data clustering. In: International conference on pattern recognition","DOI":"10.1109\/ICPR.2006.754"},{"key":"9642_CR32","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-540-78981-9_1","volume":"126","author":"A Fred","year":"2008","unstructured":"Fred A, Lourenco A (2008) Cluster ensemble methods: from single clusterings to combined solutions. Stud Comput Intell (SCI) 126:3\u201330","journal-title":"Stud Comput Intell (SCI)"},{"key":"9642_CR33","unstructured":"Fridlyand J, Dudoit S (2001) Applications of resampling methods to estimate the number of clusters and to improve the accuracy of a clustering method. Statistics Berkeley Technical Report, no. 600"},{"issue":"4","key":"9642_CR34","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1007\/s10462-010-9195-5","volume":"35","author":"R Ghaemi","year":"2011","unstructured":"Ghaemi R, ben Sulaiman N, Ibrahim H, Mustapha N (2011) A review: accuracy optimization in clustering ensembles using genetic algorithms. Artif Intell Rev 35(4):287\u2013318","journal-title":"Artif Intell Rev"},{"issue":"4","key":"9642_CR35","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1002\/widm.32","volume":"1","author":"J Ghosh","year":"2011","unstructured":"Ghosh J, Acharya A (2011) Cluster ensembles. Data Min Knowl Discov 1(4):305\u2013315","journal-title":"Data Min Knowl Discov"},{"key":"9642_CR36","doi-asserted-by":"crossref","unstructured":"Gullo F, Domeniconi C, Tagarelli A (2010) Enhancing single-objective projective clustering ensembles. In: IEEE international conference on data mining (ICDM), pp 833\u2013838","DOI":"10.1109\/ICDM.2010.138"},{"key":"9642_CR37","doi-asserted-by":"crossref","unstructured":"Gullo F, Domeniconi C, Tagarelli A (2012) Projective clustering ensembles. Data Min Knowl Discov (online)","DOI":"10.1007\/s10618-012-0266-x"},{"key":"9642_CR38","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1016\/j.neucom.2014.05.094","volume":"170","author":"D Huang","year":"2015","unstructured":"Huang D, Lai JH, Wang CD (2015) Combining multiple clusterings via crowd agreement estimation and multi-granularity link analysis. Neurocomputing 170:240\u2013250","journal-title":"Neurocomputing"},{"key":"9642_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TCYB.2017.2702343","volume":"99","author":"D Huang","year":"2017","unstructured":"Huang D, Wang CD, Lai JH (2017) Locally weighted ensemble clustering. IEEE Trans Cybern 99:1\u201314. https:\/\/doi.org\/10.1109\/TCYB.2017.2702343","journal-title":"IEEE Trans Cybern"},{"issue":"12","key":"9642_CR40","doi-asserted-by":"publisher","first-page":"2396","DOI":"10.1109\/TPAMI.2011.84","volume":"33","author":"N Iam-On","year":"2011","unstructured":"Iam-On N (2011) A link-based approach to the cluster ensemble problem. IEEE Trans Pattern Anal Mach Intell 33(12):2396\u20132409","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9642_CR41","doi-asserted-by":"crossref","unstructured":"Iam-On N, Boongoen T, Garrett S (2008) Refining pairwise similarity matrix for cluster ensemble problem with cluster relations. In: Proceedings of international conference on discovery science (ICDS), pp 222\u2013233","DOI":"10.1007\/978-3-540-88411-8_22"},{"key":"9642_CR42","doi-asserted-by":"crossref","unstructured":"Inokuchi R, Nakamura T, Miyamoto S (2006) Kernelized cluster validity measures and application to evaluation of different clustering algorithms. In: IEEE International conference on fuzzy systems, Canada, July 16\u201321","DOI":"10.1109\/FUZZY.2006.1681796"},{"issue":"4","key":"9642_CR43","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1109\/TCYB.2014.2334595","volume":"45","author":"Y Jiang","year":"2015","unstructured":"Jiang Y, Chung FL, Wang S, Deng Z, Wang J, Qian P (2015) Collaborative fuzzy clustering from multiple weighted views. IEEE Trans Cybern 45(4):688\u2013701","journal-title":"IEEE Trans Cybern"},{"issue":"6","key":"9642_CR44","doi-asserted-by":"publisher","first-page":"1299","DOI":"10.1162\/089976604773717621","volume":"16","author":"T Lange","year":"2004","unstructured":"Lange T, Roth V, Braun ML, Buhmann JM (2004) Stability-based validation of clustering solutions. Neural Comput 16(6):1299\u20131323","journal-title":"Neural Comput"},{"key":"9642_CR45","doi-asserted-by":"crossref","unstructured":"Law MHC, Topchy AP, Jain AK (2004) Multiobjective data clustering. In: IEEE conference on computer vision and pattern recognition, vol 2, pp 424\u2013430","DOI":"10.1109\/CVPR.2004.1315194"},{"key":"9642_CR46","doi-asserted-by":"crossref","unstructured":"Liu H, Liu T, Wu J, Tao D, Fu Y (2015) Spectral ensemble clustering, KDD\u201915 Sydney, Australia, pp 715\u2013724","DOI":"10.1145\/2783258.2783287"},{"issue":"5","key":"9642_CR47","doi-asserted-by":"publisher","first-page":"1129","DOI":"10.1109\/TKDE.2017.2650229","volume":"29","author":"H Liu","year":"2017","unstructured":"Liu H, Wu J, Liu T, Tao D, Fu Y (2017) Spectral ensemble clustering via weighted k-means: theoretical and practical evidence. IEEE Trans Knowl Data Eng 29(5):1129\u20131143","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"9642_CR48","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1007\/978-3-642-38067-9_16","volume-title":"Multiple classifier systems","author":"X Lu","year":"2013","unstructured":"Lu X, Yang Y, Wang H (2013) Selective clustering ensemble based on covariance. In: Zhou ZH, Roli F, Kittler J (eds) Multiple classifier systems. Springer, Berlin, pp 179\u2013189"},{"key":"9642_CR49","unstructured":"Marxer R, Holonowicz P, Purwins H, Hazan A (2007) Dynamical hierarchical self-organization of harmonic motivic, and pitch categories. In: Music, brain and cognition, part 2: models of sound and cognition, held at NIPS"},{"key":"9642_CR50","doi-asserted-by":"crossref","unstructured":"Minaei-Bidgoli B, Topchy A, Punch WF (2004) Ensembles of partitions via data resampling. In: International conference on information technology, ITCC 04, Las Vegas, pp 188\u2013192","DOI":"10.1109\/ITCC.2004.1286629"},{"key":"9642_CR51","doi-asserted-by":"crossref","unstructured":"Minaei-Bidgoli B, Parvin H, Alinejad-Rokny H, Alizadeh H, Punch WF (2011) Effects of resampling method and adaptation on clustering ensemble efficacy. Artif Intell Rev (online)","DOI":"10.1007\/s10462-011-9295-x"},{"issue":"2","key":"9642_CR52","doi-asserted-by":"publisher","first-page":"139","DOI":"10.3233\/IDA-2006-10204","volume":"10","author":"U M\u00f6ller","year":"2006","unstructured":"M\u00f6ller U, Radke D (2006) Performance of data resampling methods for robust class discovery based on clustering. Intell Data Anal 10(2):139\u2013162","journal-title":"Intell Data Anal"},{"issue":"1","key":"9642_CR53","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1137\/0105003","volume":"5","author":"J Munkres","year":"1957","unstructured":"Munkres J (1957) Algorithms for the assignment and transportation problems. J Soc Ind Appl Math 5(1):32\u201338","journal-title":"J Soc Ind Appl Math"},{"issue":"2","key":"9642_CR54","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1007\/s10618-012-0290-x","volume":"27","author":"MC Naldi","year":"2013","unstructured":"Naldi MC, De Carvalho ACM, 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":"9642_CR55","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-017-0676-x","author":"A Nazari","year":"2017","unstructured":"Nazari A, Dehghan A, Nejatian S, Rezaie V, Parvin H (2017) A comprehensive study of clustering ensemble weighting based on cluster quality and diversity. Pattern Anal Appl. https:\/\/doi.org\/10.1007\/s10044-017-0676-x","journal-title":"Pattern Anal Appl"},{"key":"9642_CR56","unstructured":"Newman CBDJ, Hettich S, Merz C (1998) UCI repository of machine learning databases. http:\/\/www.ics.uci.edu\/\u02dcmlearn\/MLSummary.html"},{"issue":"2","key":"9642_CR57","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1007\/s11634-013-0130-x","volume":"7","author":"H Parvin","year":"2013","unstructured":"Parvin H, Minaei-Bidgoli B (2013) A clustering ensemble framework based on elite selection of weighted clusters. Adv Data Anal Classif 7(2):181\u2013208","journal-title":"Adv Data Anal Classif"},{"issue":"1","key":"9642_CR58","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/s10044-013-0364-4","volume":"18","author":"H Parvin","year":"2015","unstructured":"Parvin H, Minaei-Bidgoli B (2015) A clustering ensemble framework based on selection of fuzzy weighted clusters in a locally adaptive clustering algorithm. Pattern Anal Appl 18(1):87\u2013112","journal-title":"Pattern Anal Appl"},{"issue":"1","key":"9642_CR59","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1109\/TLT.2011.22","volume":"5","author":"N Pattanasri","year":"2012","unstructured":"Pattanasri N (2012) Learning to estimate slide comprehension in classrooms with support vector machines. IEEE Trans Learn Technol 5(1):52\u201361","journal-title":"IEEE Trans Learn Technol"},{"issue":"10","key":"9642_CR60","doi-asserted-by":"publisher","first-page":"2685","DOI":"10.1016\/j.patcog.2013.03.006","volume":"46","author":"G Rafiee","year":"2013","unstructured":"Rafiee G, Dlay SS, Woo WL (2013) Region-of-interest extraction in low depth of field images using ensemble clustering and difference of Gaussian approaches. Pattern Recogn 46(10):2685\u20132699","journal-title":"Pattern Recogn"},{"key":"9642_CR61","doi-asserted-by":"crossref","unstructured":"Rakhlin A, Caponnetto A (2007) Stability of k-means clustering. In: Sch\u00f6lkopf B, Platt J, Hoffman T (eds) Advances in neural information processing systems, vol 19. MIT Press, Cambridge","DOI":"10.7551\/mitpress\/7503.003.0145"},{"key":"9642_CR62","unstructured":"Roth V, Lange T (2004) Feature selection in clustering problems. Advances in neural information processing systems, pp 473\u2013480"},{"key":"9642_CR63","doi-asserted-by":"crossref","unstructured":"Roth V, Lange T, Braun M, Buhmann J (2002) A resampling approach to cluster validation. In: International conference on computational statistics, COMPSTAT","DOI":"10.1007\/978-3-642-57489-4_13"},{"issue":"12","key":"9642_CR64","doi-asserted-by":"publisher","first-page":"2682","DOI":"10.1109\/TCYB.2014.2313638","volume":"44","author":"V Soto","year":"2014","unstructured":"Soto V, Garcia-Moratilla S, Martinez-Munoz G, Hernandez- Lobato D, Suarez A (2014) A double pruning scheme for boosting ensembles. IEEE Trans Cybern 44(12):2682\u20132695","journal-title":"IEEE Trans Cybern"},{"issue":"Dec","key":"9642_CR65","first-page":"583","volume":"3","author":"A Strehl","year":"2002","unstructured":"Strehl A, Ghosh J (2002) Cluster ensembles-a knowledge reuse framework for combining multiple partitions. J Mach Learn Res 3(Dec):583\u2013617","journal-title":"J Mach Learn Res"},{"key":"9642_CR66","doi-asserted-by":"crossref","unstructured":"Topchy AP, Jain AK, Punch WF (2003) Combining multiple weak clusterings. In: IEEE international conference on data mining, pp 331\u2013338","DOI":"10.1109\/ICDM.2003.1250937"},{"issue":"4","key":"9642_CR67","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/T-AFFC.2011.12","volume":"2","author":"J Wagner","year":"2011","unstructured":"Wagner J (2011) Exploring fusion methods for multimodal emotion recognition with missing data. IEEE Trans Affect Comput 2(4):206\u2013218","journal-title":"IEEE Trans Affect Comput"},{"key":"9642_CR68","unstructured":"Wang X, Han D, Han C (2013) Rough set based cluster ensemble selection. In: Proceedings of the 16th international conference on information fusion, pp 438\u2013444"},{"issue":"1","key":"9642_CR69","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1109\/T-AFFC.2010.16","volume":"2","author":"CH Wu","year":"2011","unstructured":"Wu CH (2011) Emotion recognition of affective speech based on multiple classifiers using acoustic\u2013prosodic information and semantic labels. IEEE Trans Affect Comput 2(1):10\u201321","journal-title":"IEEE Trans Affect Comput"},{"issue":"4","key":"9642_CR70","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1109\/34.85677","volume":"13","author":"XL Xie","year":"1991","unstructured":"Xie XL, Beni G (1991) A validity measure for fuzzy clustering. IEEE Trans Pattern Anal Mach Intell 13(4):841\u2013846","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9642_CR71","doi-asserted-by":"crossref","unstructured":"Yousefnezhad M, Zhang D (2015) Weighted spectral cluster ensemble. In: ICDM 2015, pp 549\u2013558","DOI":"10.1109\/ICDM.2015.145"},{"key":"9642_CR72","first-page":"1","volume":"99","author":"M Yousefnezhad","year":"2017","unstructured":"Yousefnezhad M, Huang SJ, Zhang D (2017) WoCE: a framework for clustering ensemble by exploiting the wisdom of crowds theory. IEEE Trans Cybern 99:1\u201314","journal-title":"IEEE Trans Cybern"},{"issue":"3","key":"9642_CR73","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1109\/TCBB.2013.59","volume":"10","author":"Z Yu","year":"2013","unstructured":"Yu Z, Chen H, You J, Han G, Li L (2013) Hybrid fuzzy cluster ensemble framework for tumor clustering from biomolecular data. IEEE\/ACM Trans Comput Biol Bioinf 10(3):657\u2013670","journal-title":"IEEE\/ACM Trans Comput Biol Bioinf"},{"issue":"10","key":"9642_CR74","doi-asserted-by":"publisher","first-page":"3362","DOI":"10.1016\/j.patcog.2014.04.005","volume":"47","author":"Z Yu","year":"2014","unstructured":"Yu Z, Li L, Gao Y, You J, Liu J, Wong HS, Han G (2014) Hybrid clustering solution selection strategy. Pattern Recogn 47(10):3362\u20133375","journal-title":"Pattern Recogn"},{"issue":"2","key":"9642_CR75","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1109\/TCYB.2014.2322195","volume":"45","author":"Z Yu","year":"2015","unstructured":"Yu Z, Li L, Liu J, Han G (2015) Hybrid adaptive classifier ensemble. IEEE Trans Cybern 45(2):177\u2013190","journal-title":"IEEE Trans Cybern"},{"issue":"6","key":"9642_CR76","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.1109\/TCYB.2015.2443857","volume":"46","author":"Z Yu","year":"2016","unstructured":"Yu Z, Chen H, Liu J, You J, Leung H, Han G (2016a) Hybrid k-nearest neighbor classifier. IEEE Trans Cybern 46(6):1263\u20131275","journal-title":"IEEE Trans Cybern"},{"key":"9642_CR77","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TCYB.2016.2569529","volume":"99","author":"Z Yu","year":"2016","unstructured":"Yu Z, Zhu X, Wong HS, You J, Zhang J, Han G (2016b) Distribution-based cluster structure selection. IEEE Trans Cybern 99:1\u201314. https:\/\/doi.org\/10.1109\/TCYB.2016.2569529","journal-title":"IEEE Trans Cybern"},{"key":"9642_CR78","first-page":"1","volume":"99","author":"Z Yu","year":"2017","unstructured":"Yu Z, Lu Y, Zhang J, You J, Wong HS, Wang Y, Han G (2017) Progressive semisupervised learning of multiple classifiers. IEEE Trans Cybern 99:1\u201314","journal-title":"IEEE Trans Cybern"},{"key":"9642_CR79","doi-asserted-by":"publisher","first-page":"2699","DOI":"10.1016\/j.patcog.2015.02.014","volume":"48","author":"C Zhong","year":"2015","unstructured":"Zhong C et al (2015) A clustering ensemble: two-level-refined co-association matrix with path-based transformation. Pattern Recogn 48:2699\u20132709","journal-title":"Pattern Recogn"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-018-9642-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10462-018-9642-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-018-9642-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,3]],"date-time":"2023-09-03T08:45:31Z","timestamp":1693730731000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10462-018-9642-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6,21]]},"references-count":79,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,8]]}},"alternative-id":["9642"],"URL":"https:\/\/doi.org\/10.1007\/s10462-018-9642-2","relation":{},"ISSN":["0269-2821","1573-7462"],"issn-type":[{"value":"0269-2821","type":"print"},{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,6,21]]},"assertion":[{"value":"21 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}