{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T08:23:46Z","timestamp":1778660626257,"version":"3.51.4"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"1-2","license":[{"start":{"date-parts":[[2013,7,3]],"date-time":"2013-07-03T00:00:00Z","timestamp":1372809600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2015,1]]},"DOI":"10.1007\/s10994-013-5394-z","type":"journal-article","created":{"date-parts":[[2013,7,2]],"date-time":"2013-07-02T13:55:50Z","timestamp":1372773350000},"page":"217-268","source":"Crossref","is-referenced-by-count":9,"title":["Unsupervised ensemble minority clustering"],"prefix":"10.1007","volume":"98","author":[{"given":"Edgar","family":"Gonz\u00e0lez","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jordi","family":"Turmo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2013,7,3]]},"reference":[{"key":"5394_CR1","unstructured":"ACE (2008). The ACE 2008 (ACE08) evaluation plan. http:\/\/www.itl.nist.gov\/iad\/mig\/tests\/ace\/2008\/doc\/ ."},{"key":"5394_CR2","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1109\/ICDM.2007.53","volume-title":"7th IEEE international conference on data mining (ICDM)","author":"S. Ando","year":"2007","unstructured":"Ando, S. (2007). Clustering needles in a haystack: an information theoretic analysis of minority and outlier detection. In 7th IEEE international conference on data mining (ICDM) (pp.\u00a013\u201322)."},{"key":"5394_CR3","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1109\/ICDM.2006.19","volume-title":"6th IEEE international conference on data mining (ICDM)","author":"S. Ando","year":"2006","unstructured":"Ando, S., & Suzuki, E. (2006). An information theoretic approach to detection of minority subsets in database. In 6th IEEE international conference on data mining (ICDM) (pp.\u00a011\u201320)."},{"key":"5394_CR4","first-page":"1705","volume":"6","author":"A. Banerjee","year":"2005","unstructured":"Banerjee, A., Merugu, S., Dhillon, I. S., & Ghosh, J. (2005). Clustering with Bregman divergences. Journal of Machine Learning Research, 6, 1705\u20131749.","journal-title":"Journal of Machine Learning Research"},{"issue":"3","key":"5394_CR5","doi-asserted-by":"crossref","first-page":"803","DOI":"10.2307\/2532201","volume":"49","author":"J. D. Banfield","year":"1993","unstructured":"Banfield, J. D., & Raftery, A. E. (1993). Model-based Gaussian and non-Gaussian clustering. Biometrics, 49(3), 803\u2013821.","journal-title":"Biometrics"},{"key":"5394_CR6","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1007\/978-3-642-52307-6_8","volume-title":"Multiple Hypothesenpr\u00fcfung\u2014multiple hypotheses testing","author":"B. Bergmann","year":"1988","unstructured":"Bergmann, B., & Hommel, G. (1988). Improvements of general multiple test procedures for redundant systems of hypotheses. In P. Bauer, G. Hommel, & E. Sonnemann (Eds.), Multiple Hypothesenpr\u00fcfung\u2014multiple hypotheses testing (pp.\u00a0100\u2013115). Berlin: Springer."},{"key":"5394_CR7","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-0450-1","volume-title":"Pattern recognition with fuzzy objective function algorithms","author":"J. C. Bezdek","year":"1981","unstructured":"Bezdek, J. C. (1981). Pattern recognition with fuzzy objective function algorithms. New York: Plenum Press."},{"issue":"7","key":"5394_CR8","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1109\/34.865189","volume":"22","author":"C. Biernacki","year":"2000","unstructured":"Biernacki, C., Celeux, G., & Govaert, G. (2000). Assessing a mixture model for clustering with the integrated completed likelihood. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(7), 719\u2013725.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"5394_CR9","first-page":"1059","volume":"3","author":"N. Cancedda","year":"2003","unstructured":"Cancedda, N., Gaussier, E., Goutte, C., & Renders, J. M. (2003). Word sequence kernels. Journal of Machine Learning Research, 3, 1059\u20131082.","journal-title":"Journal of Machine Learning Research"},{"key":"5394_CR10","doi-asserted-by":"crossref","first-page":"15:1","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V. Chandola","year":"2009","unstructured":"Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection: a survey. ACM Computing Surveys, 41, 15:1\u201358.","journal-title":"ACM Computing Surveys"},{"issue":"8","key":"5394_CR11","doi-asserted-by":"crossref","first-page":"790","DOI":"10.1109\/34.400568","volume":"17","author":"Y. Cheng","year":"1995","unstructured":"Cheng, Y. (1995). Mean shift, mode seeking, and clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(8), 790\u2013799.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"5394_CR12","first-page":"263","volume-title":"40th annual meeting of the association for computational linguistics (ACL)","author":"M. Collins","year":"2002","unstructured":"Collins, M., & Duffy, N. (2002). New ranking algorithms for parsing and tagging: kernels over discrete structures, and the voted perceptron. In 40th annual meeting of the association for computational linguistics (ACL) (pp.\u00a0263\u2013270)."},{"key":"5394_CR13","first-page":"26","volume-title":"21st international conference on machine learning (ICML)","author":"K. Crammer","year":"2004","unstructured":"Crammer, K., & Chechik, G. (2004). A needle in a haystack: local one-class optimization. In 21st international conference on machine learning (ICML) (pp.\u00a026\u201333)."},{"key":"5394_CR14","first-page":"265","volume":"2","author":"K. Crammer","year":"2001","unstructured":"Crammer, K., & Singer, Y. (2001). On the algorithmic implementation of multiclass kernel-based vector machines. Journal of Machine Learning Research, 2, 265\u2013292.","journal-title":"Journal of Machine Learning Research"},{"key":"5394_CR15","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1145\/1390156.1390180","volume-title":"25th international conference on machine learning (ICML)","author":"K. Crammer","year":"2008","unstructured":"Crammer, K., Talukdar, P. P., & Pereira, F. C. (2008). A rate-distortion one-class model and its applications to clustering. In 25th international conference on machine learning (ICML) (pp.\u00a0184\u2013191)."},{"issue":"11","key":"5394_CR16","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1016\/0167-8655(91)90002-4","volume":"12","author":"R. N. Dav\u00e9","year":"1991","unstructured":"Dav\u00e9, R. N. (1991). Characterization and detection of noise in clustering. Pattern Recognition Letters, 12(11), 657\u2013664.","journal-title":"Pattern Recognition Letters"},{"key":"5394_CR17","doi-asserted-by":"crossref","unstructured":"Dav\u00e9, R. N., & Krishnapuram, R. (1997). Robust clustering methods: a unified view. IEEE Transactions on Fuzzy Systems, 5(2).","DOI":"10.1109\/91.580801"},{"key":"5394_CR18","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1145\/1143844.1143874","volume-title":"23rd international conference on machine learning (ICML)","author":"J. Davis","year":"2006","unstructured":"Davis, J., & Goadrich, M. (2006). The relationship between precision-recall and ROC curves. In 23rd international conference on machine learning (ICML) (pp.\u00a0233\u2013240)."},{"key":"5394_CR19","volume-title":"6th symposium on operating system design and implementation","author":"J. Dean","year":"2004","unstructured":"Dean, J., & Ghemawat, S. (2004). Mapreduce: simplified data processing on large clusters. In 6th symposium on operating system design and implementation."},{"key":"5394_CR20","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/S0165-0114(02)00220-8","volume":"137","author":"P. J. Deer","year":"2003","unstructured":"Deer, P. J., & Eklund, P. (2003). A study of parameter values for a Mahalanobis distance fuzzy classifier. Fuzzy Sets and Systems, 137, 191\u2013213.","journal-title":"Fuzzy Sets and Systems"},{"key":"5394_CR21","doi-asserted-by":"crossref","unstructured":"Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Royal Statistical Society, Series B, 39(1).","DOI":"10.1111\/j.2517-6161.1977.tb01600.x"},{"key":"5394_CR22","first-page":"1","volume":"7","author":"J. Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar, J. (2006). Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, 7, 1\u201330.","journal-title":"Journal of Machine Learning Research"},{"key":"5394_CR23","first-page":"113","volume-title":"Advances in computers","author":"R. Dubes","year":"1980","unstructured":"Dubes, R., & Jain, A. K. (1980). Clustering methodologies in exploratory data analysis. In M. C. Yovits (Ed.), Advances in computers (Vol.\u00a019, pp.\u00a0113\u2013228). Amsterdam: Elsevier."},{"key":"5394_CR24","first-page":"226","volume-title":"2nd ACM SIGKDD international conference on knowledge discovery and data mining (KDD)","author":"M. Ester","year":"1996","unstructured":"Ester, M., Kriegel, H. P., Sander, J., & Xu, X. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. In 2nd ACM SIGKDD international conference on knowledge discovery and data mining (KDD) (pp.\u00a0226\u2013231)."},{"issue":"8","key":"5394_CR25","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","volume":"27","author":"T. Fawcett","year":"2006","unstructured":"Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861\u2013874.","journal-title":"Pattern Recognition Letters"},{"issue":"8","key":"5394_CR26","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1093\/comjnl\/41.8.578","volume":"41","author":"C. Fraley","year":"1998","unstructured":"Fraley, C., & Raftery, A. E. (1998). How many clusters? Which clustering method? Answers via model-based cluster analysis. Computer Journal, 41(8), 578\u2013588.","journal-title":"Computer Journal"},{"issue":"3","key":"5394_CR27","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1023\/A:1007662407062","volume":"37","author":"Y. Freund","year":"1999","unstructured":"Freund, Y., & Schapire, R. E. (1999). Large margin classification using the perceptron algorithm. Machine Learning, 37(3), 277\u2013296.","journal-title":"Machine Learning"},{"issue":"1","key":"5394_CR28","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/TIT.1975.1055330","volume":"21","author":"K. Fukunaga","year":"1975","unstructured":"Fukunaga, K., & Hostetler, L. D. (1975). The estimation of the gradient of a density function, with applications in pattern recognition. IEEE Transactions on Information Theory, 21(1), 32\u201340.","journal-title":"IEEE Transactions on Information Theory"},{"key":"5394_CR29","first-page":"2677","volume":"9","author":"S. Garc\u00eda","year":"2008","unstructured":"Garc\u00eda, S., & Herrera, F. (2008). An extension on \u201cStatistical comparisons of classifiers over multiple data sets\u201d for all pairwise comparisons. Journal of Machine Learning Research, 9, 2677\u20132694.","journal-title":"Journal of Machine Learning Research"},{"key":"5394_CR30","volume-title":"Data mining: foundations and intelligent paradigms","author":"J. Ghosh","year":"2011","unstructured":"Ghosh, J., & Gupta, G. (2011). Bregman bubble clustering: a robust framework for mining dense clusters. In D. Holmes & L. C. Jain (Eds.), Data mining: foundations and intelligent paradigms. Berlin: Springer."},{"key":"5394_CR31","first-page":"99","volume-title":"NSF workshop on next generation data mining","author":"J. Ghosh","year":"2002","unstructured":"Ghosh, J., Strehl, A., & Merugu, S. (2002). A consensus framework for integrating distributed clusterings under limited knowledge sharing. In NSF workshop on next generation data mining (pp.\u00a099\u2013108)."},{"key":"5394_CR32","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1109\/ICDE.2005.34","volume-title":"21st IEEE international conference on data engineering (ICDE)","author":"A. Gionis","year":"2005","unstructured":"Gionis, A., Mannila, H., & Tsaparas, P. (2005). Clustering aggregation. In 21st IEEE international conference on data engineering (ICDE) (pp.\u00a0341\u2013352)."},{"issue":"3","key":"5394_CR33","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1109\/TNN.2002.1000150","volume":"13","author":"M. Girolami","year":"2002","unstructured":"Girolami, M. (2002). Mercer kernel-based clustering in feature space. IEEE Transactions on Neural Networks, 13(3), 780\u2013784.","journal-title":"IEEE Transactions on Neural Networks"},{"key":"5394_CR34","unstructured":"Gonz\u00e0lez, E. (2012). Unsupervised learning of relation detection patterns. PhD thesis, Department de Llenguatges i Sistemes Inform\u00e0tics, Universitat Polit\u00e8cnica de Catalunya."},{"key":"5394_CR35","first-page":"782","volume-title":"9th IEEE international conference on data mining (ICDM)","author":"E. Gonz\u00e0lez","year":"2009","unstructured":"Gonz\u00e0lez, E., & Turmo, J. (2009). Unsupervised relation extraction by massive clustering. In 9th IEEE international conference on data mining (ICDM) (pp.\u00a0782\u2013787)."},{"key":"5394_CR36","unstructured":"Graff, D. (2002). The AQUAINT corpus of English news text (Tech. Rep. LDC2002T31). Linguistic Data Consortium."},{"issue":"3","key":"5394_CR37","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1109\/42.585758","volume":"16","author":"R. Guillemaud","year":"1997","unstructured":"Guillemaud, R., & Brady, M. (1997). Estimating the bias field of MR images. IEEE Transactions on Medical Imaging, 16(3), 238\u2013251.","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"5394_CR38","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1145\/1102351.1102386","volume-title":"22nd international conference on machine learning (ICML)","author":"G. Gupta","year":"2005","unstructured":"Gupta, G., & Ghosh, J. (2005). Robust one-class clustering using hybrid global and local search. In 22nd international conference on machine learning (ICML) (pp.\u00a0273\u2013280)."},{"key":"5394_CR39","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1109\/ICDM.2006.32","volume-title":"6th IEEE international conference on data mining (ICDM)","author":"G. Gupta","year":"2006","unstructured":"Gupta, G., & Ghosh, J. (2006). Bregman bubble clustering: a robust, scalable framework for locating multiple, dense regions in data. In 6th IEEE international conference on data mining (ICDM) (pp.\u00a0232\u2013243)."},{"issue":"2","key":"5394_CR40","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1109\/TCBB.2008.32","volume":"7","author":"G. Gupta","year":"2010","unstructured":"Gupta, G., Liu, A., & Ghosh, J. (2010). Automated hierarchical density shaving: a robust automated clustering and visualization framework for large biological data sets. IEEE\/ACM Transactions on Computational Biology and Bioinformatics, 7(2), 223\u2013237.","journal-title":"IEEE\/ACM Transactions on Computational Biology and Bioinformatics"},{"key":"5394_CR41","volume-title":"Conference on empirical methods in natural language processing (EMNLP)","author":"H. Hassan","year":"2006","unstructured":"Hassan, H., Hassan, A., & Emam, O. (2006). Unsupervised information extraction approach using graph mutual reinforcement. In Conference on empirical methods in natural language processing (EMNLP)."},{"key":"5394_CR42","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1023\/B:AIRE.0000045502.10941.a9","volume":"22","author":"V. Hodge","year":"2004","unstructured":"Hodge, V., & Austin, J. (2004). A survey of outlier detection methodologies. Artificial Intelligence Review, 22, 85\u2013126.","journal-title":"Artificial Intelligence Review"},{"issue":"3","key":"5394_CR43","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1145\/331499.331504","volume":"31","author":"A. K. Jain","year":"1999","unstructured":"Jain, A. K., Murty, M. N., & Flynn, P. J. (1999). Data clustering: a review. ACM Computing Surveys, 31(3), 264\u2013323.","journal-title":"ACM Computing Surveys"},{"key":"5394_CR44","volume-title":"Finding groups in data: an introduction to cluster analysis","author":"L. Kaufman","year":"2005","unstructured":"Kaufman, L., & Rousseeuw, P. J. (2005). Finding groups in data: an introduction to cluster analysis. New York: Wiley."},{"key":"5394_CR45","volume-title":"Fuzzy sets and fuzzy logic: theory and applications","author":"G. J. Klir","year":"1995","unstructured":"Klir, G. J., & Yuan, B. (1995). Fuzzy sets and fuzzy logic: theory and applications. New York: Prentice Hall."},{"key":"5394_CR46","first-page":"281","volume-title":"5th Berkeley symposium on mathematical statistics and probability","author":"J. B. MacQueen","year":"1967","unstructured":"MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations. In 5th Berkeley symposium on mathematical statistics and probability (pp.\u00a0281\u2013297)."},{"key":"5394_CR47","first-page":"797","volume-title":"World congress on neural networks","author":"M. M. Moya","year":"1993","unstructured":"Moya, M. M., Koch, M. W., & Hostetler, L. D. (1993). One-class classifier networks for target recognition applications. In World congress on neural networks (pp.\u00a0797\u2013801)."},{"key":"5394_CR48","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.ecoinf.2005.10.006","volume":"1","author":"F. Okeke","year":"2006","unstructured":"Okeke, F., & Karnieli, A. (2006). Linear mixture model approach for selecting fuzzy exponent value in fuzzy c-Means algorithm. Ecological Informatics, 1, 117\u2013124.","journal-title":"Ecological Informatics"},{"key":"5394_CR49","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1023\/A:1008981510081","volume":"10","author":"D. Peel","year":"2000","unstructured":"Peel, D., & McLachlan, G. J. (2000). Robust mixture modelling using the t distribution. Statistics and Computing, 10, 339\u2013348.","journal-title":"Statistics and Computing"},{"issue":"3","key":"5394_CR50","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1108\/eb046814","volume":"14","author":"M. F. Porter","year":"1980","unstructured":"Porter, M. F. (1980). An algorithm for suffix stripping. Program, 14(3), 130\u2013137.","journal-title":"Program"},{"issue":"7","key":"5394_CR51","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1162\/089976601750264965","volume":"13","author":"B. Sch\u00f6lkopf","year":"2001","unstructured":"Sch\u00f6lkopf, B., Platt, J. C., Shawe-Taylor, J., Smola, A. J., & Williamson, R. C. (2001). Estimating the support of a high-dimensional distribution. Neural Computation, 13(7), 1443\u20131471.","journal-title":"Neural Computation"},{"issue":"22","key":"5394_CR52","doi-asserted-by":"crossref","first-page":"2841","DOI":"10.1093\/bioinformatics\/btq534","volume":"26","author":"V. Schw\u00e4mmle","year":"2010","unstructured":"Schw\u00e4mmle, V., & Jensen, O. N. (2010). A simple and fast method to determine the parameters for fuzzy c-Means cluster analysis. Bioinformatics, 26(22), 2841\u20132848.","journal-title":"Bioinformatics"},{"issue":"2","key":"5394_CR53","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G. E. Schwartz","year":"1978","unstructured":"Schwartz, G. E. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461\u2013464.","journal-title":"The Annals of Statistics"},{"key":"5394_CR54","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511809682","volume-title":"Kernel methods for pattern analysis","author":"J. Shawe-Taylor","year":"2004","unstructured":"Shawe-Taylor, J., & Cristianini, N. (2004). Kernel methods for pattern analysis. Cambridge: Cambridge University Press."},{"key":"5394_CR55","first-page":"208","volume-title":"23rd annual international ACM SIGIR conference on research and development in information retrieval","author":"N. Slonim","year":"2000","unstructured":"Slonim, N., & Tishby, N. (2000). Document clustering using word clusters via the information bottleneck method. In 23rd annual international ACM SIGIR conference on research and development in information retrieval (pp.\u00a0208\u2013215)."},{"key":"5394_CR56","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1108\/eb026526","volume":"28","author":"K. Sp\u00e4rck-Jones","year":"1972","unstructured":"Sp\u00e4rck-Jones, K. (1972). A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28, 11\u201321.","journal-title":"Journal of Documentation"},{"key":"5394_CR57","first-page":"583","volume":"3","author":"A. Strehl","year":"2002","unstructured":"Strehl, A., & Ghosh, J. (2002). Cluster ensembles\u2014a knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research, 3, 583\u2013617.","journal-title":"Journal of Machine Learning Research"},{"key":"5394_CR58","volume-title":"Introduction to data mining","author":"P. N. Tan","year":"2005","unstructured":"Tan, P. N., Steinbach, M., & Kumar, V. (2005). Introduction to data mining. Reading: Addison-Wesley."},{"issue":"1","key":"5394_CR59","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1023\/B:MACH.0000008084.60811.49","volume":"54","author":"D. M. Tax","year":"2004","unstructured":"Tax, D. M., & Duin, R. P. (2004). Support vector data description. Machine Learning, 54(1), 45\u201366.","journal-title":"Machine Learning"},{"key":"5394_CR60","volume-title":"37th Allerton conference on communication, control, and computing","author":"N. Tishby","year":"1999","unstructured":"Tishby, N., Pereira, F. C., & Bialek, W. (1999). The information bottleneck method. In 37th Allerton conference on communication, control, and computing."},{"key":"5394_CR61","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1109\/ICDM.2003.1250937","volume-title":"3rd IEEE international conference on data mining (ICDM)","author":"A. Topchy","year":"2003","unstructured":"Topchy, A., Jain, A. K., & Punch, W. (2003). Combining multiple weak clusterings. In 3rd IEEE international conference on data mining (ICDM) (pp.\u00a0331\u2013338)."},{"key":"5394_CR62","first-page":"379","volume-title":"SIAM international conference on data mining (SDM)","author":"A. Topchy","year":"2004","unstructured":"Topchy, A., Jain, A. K., & Punch, W. (2004). A mixture model for clustering ensembles. In SIAM international conference on data mining (SDM) (pp.\u00a0379\u2013390)."},{"issue":"12","key":"5394_CR63","doi-asserted-by":"crossref","first-page":"1866","DOI":"10.1109\/TPAMI.2005.237","volume":"27","author":"A. Topchy","year":"2005","unstructured":"Topchy, A., Jain, A. K., & Punch, W. (2005). Clustering ensembles: models of consensus and weak partitions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(12), 1866\u20131881.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"5394_CR64","first-page":"282","volume-title":"Colloquium on numerical taxonomy","author":"D. Wishart","year":"1969","unstructured":"Wishart, D. (1969). Mode analysis: a generalization of nearest neighbour which reduces chaining effects. In Colloquium on numerical taxonomy (pp.\u00a0282\u2013308)."},{"issue":"3","key":"5394_CR65","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1109\/TNN.2005.845141","volume":"16","author":"R. Xu","year":"2005","unstructured":"Xu, R., & Wunsch, D. C. II (2005). Survey of clustering algorithms. IEEE Transactions on Neural Networks, 16(3), 645\u2013678.","journal-title":"IEEE Transactions on Neural Networks"},{"key":"5394_CR66","doi-asserted-by":"crossref","unstructured":"Yu, J., Cheng, Q., & Huang, H. (2004). Analysis of the weighting exponent in the FCM. IEEE Transactions on Systems, Man, and Cybernetics, Part\u00a0B: Cybernetics, 34.","DOI":"10.1109\/TSMCB.2003.810951"},{"issue":"3","key":"5394_CR67","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/S0019-9958(65)90241-X","volume":"8","author":"L. A. Zadeh","year":"1965","unstructured":"Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338\u2013353.","journal-title":"Information and Control"},{"key":"5394_CR68","first-page":"103","volume-title":"ACM SIGMOD international conference on management of data","author":"T. Zhang","year":"1996","unstructured":"Zhang, T., Ramakrishnan, R., & Livny, M. (1996). BIRCH: an efficient data clustering method for very large databases. In ACM SIGMOD international conference on management of data (pp.\u00a0103\u2013114)."},{"key":"5394_CR69","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1023\/B:MACH.0000027785.44527.d6","volume":"55","author":"Y. Zhao","year":"2004","unstructured":"Zhao, Y., & Karypis, G. (2004). Empirical and theoretical comparisons of selected criterion functions for document clustering. Machine Learning, 55, 311\u2013331.","journal-title":"Machine Learning"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-013-5394-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-013-5394-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-013-5394-z","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T23:14:47Z","timestamp":1563318887000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-013-5394-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,7,3]]},"references-count":69,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2015,1]]}},"alternative-id":["5394"],"URL":"https:\/\/doi.org\/10.1007\/s10994-013-5394-z","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,7,3]]}}}