{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T20:16:40Z","timestamp":1742933800639,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319015941"},{"type":"electronic","value":"9783319015958"}],"license":[{"start":{"date-parts":[[2013,10,10]],"date-time":"2013-10-10T00:00:00Z","timestamp":1381363200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2013,10,10]],"date-time":"2013-10-10T00:00:00Z","timestamp":1381363200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-01595-8_23","type":"book-chapter","created":{"date-parts":[[2013,11,26]],"date-time":"2013-11-26T07:32:57Z","timestamp":1385451177000},"page":"209-216","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Symbolic Cluster Ensemble based on Co-Association Matrix versus Noisy Variables and Outliers"],"prefix":"10.1007","author":[{"given":"Marcin","family":"Pe\u0142ka","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2013,10,10]]},"reference":[{"key":"23_CR1","doi-asserted-by":"publisher","DOI":"10.1002\/9780470090183","volume-title":"Symbolic data analysis. Conceptual statistics and data Mining","author":"L. Billard","year":"2006","unstructured":"Billard, L., & Diday, E. (2006). Symbolic data analysis. Conceptual statistics and data Mining. Chichester: Wiley."},{"volume-title":"Analysis of symbolic data. Explanatory methods for extracting statistical information from complex data","year":"2000","key":"23_CR2","unstructured":"Bock, H.-H., & Diday, E. (Eds.). (2000). Analysis of symbolic data. Explanatory methods for extracting statistical information from complex data. Berlin: Springer."},{"issue":"1","key":"23_CR3","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1016\/j.patcog.2011.05.016","volume":"45","author":"F. A. T. De Carvalho","year":"2012","unstructured":"De Carvalho, F. A. T., Lechevallier, Y., & De Melo, F. M. (2012). Partitioning hard clustering algorithms based on multiple dissimilarity matrices. Pattern Recognition 45(1), 447\u2013464.","journal-title":"Pattern Recognition"},{"issue":"3","key":"23_CR4","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.patrec.2005.08.014","volume":"27","author":"F. A. T. De Carvalho","year":"2006","unstructured":"De Carvalho, F. A. T., Souza, R. M. C. R., Chavent, M., & Lechevalier, Y. (2006). Adaptive Hausdorff distances and dynamic clustering of symbolic data. Pattern Recognition Letters 27(3): 167\u2013179.","journal-title":"Pattern Recognition Letters"},{"key":"23_CR5","volume-title":"Finding consistent clusters in data partitions. In J. Kittler & F. Roli (Eds.), Multiple classifier systems, Vol. 1857 of Lecture Notes in Computer Science (pp. 78\u201386)","author":"A. L. N. Fred","year":"2001","unstructured":"Fred, A. L. N. (2001). Finding consistent clusters in data partitions. In J. Kittler & F. Roli (Eds.), Multiple classifier systems, Vol.\u00a01857 of Lecture Notes in Computer Science (pp. 78\u201386). Berlin: Springer."},{"key":"23_CR6","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1109\/TPAMI.2005.113","volume":"27","author":"A. L. N. Fred","year":"2005","unstructured":"Fred, A. L. N., & Jain, A. K. (2005). Combining multiple clustering using evidence accumulation. IEEE Transaction on Pattern Analysis and Machine Intelligence, 27, 835\u2013850.","journal-title":"IEEE Transaction on Pattern Analysis and Machine Intelligence"},{"key":"23_CR7","volume-title":"Metody statystycznej analizy wielowymiarowej w badaniach marketingowych. [Multivariate statistical methods in marketing researches]","author":"E. Gatnar","year":"2004","unstructured":"Gatnar, E., & Walesiak, M. (2004). Metody statystycznej analizy wielowymiarowej w badaniach marketingowych. [Multivariate statistical methods in marketing researches]. Wroc\u0142aw University of Economics, Wroc\u0142aw."},{"key":"23_CR8","first-page":"636","volume":"38","author":"R. Ghaemi","year":"2009","unstructured":"Ghaemi, R., Sulaiman, N., Ibrahim, H., & Mustapha, N. (2009). A survey: Clustering ensemble techniques. Proceedings of World Academy of Science, Engineering and Technology, 38, 636\u2013645.","journal-title":"Proceedings of World Academy of Science, Engineering and Technology"},{"key":"23_CR9","doi-asserted-by":"crossref","DOI":"10.1201\/9780367805302","volume-title":"Classification","author":"A. D. Gordon","year":"1999","unstructured":"Gordon, A. D. (1999). Classification. Boca Raton: Chapman and Hall\/CRC."},{"key":"23_CR10","doi-asserted-by":"crossref","first-page":"65","DOI":"10.18637\/jss.v014.i12","volume":"14","author":"K. Hornik","year":"2005","unstructured":"Hornik, K. (2005). A CLUE for CLUster ensembles. Journal of Statistical Software, 14, 65\u201372.","journal-title":"Journal of Statistical Software"},{"key":"23_CR11","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BF01908075","volume":"1","author":"L. Hubert","year":"1985","unstructured":"Hubert, L., & Arabie, P. (1985). Comparing partitions. Journal of Classification, 1, 193\u2013218.","journal-title":"Journal of Classification"},{"issue":"3","key":"23_CR12","doi-asserted-by":"publisher","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 Computational Surveys, 31(3), 264\u2013323.","journal-title":"ACM Computational Surveys"},{"key":"23_CR13","unstructured":"Leisch, F., & Dimitriadou, E. (2010). The mlbench package. http:\/\/www.R-project.org\/."},{"issue":"2","key":"23_CR14","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1007\/BF02294245","volume":"50","author":"G. W. Milligan","year":"1985","unstructured":"Milligan, G. W., & Cooper, M. C. (1985). An examination of procedures for determining the number of clusters in a data set. Psychometrika, 50(2), 159\u2013179.","journal-title":"Psychometrika"},{"key":"23_CR15","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1007\/978-3-642-10745-0_37","volume-title":"Classification as a tool for research","author":"M. Pelka","year":"2010","unstructured":"Pelka, M. (2010). Symbolic multidimensional scaling versus noisy variables and outliers. In\u00a0H.\u00a0Locarek-Junge & C. Weihs (Eds.), Classification as a tool for research (pp. 341\u2013350). Berlin: Springer."},{"key":"23_CR16","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1007\/s00357-006-0018-y","volume":"23","author":"W. Qiu","year":"2006","unstructured":"Qiu, W., & Joe, H. (2006). Generation of random clusters with specified degree of separation. Journal of Classification, 23, 315\u2013334.","journal-title":"Journal of Classification"},{"key":"23_CR17","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"P. J. Rousseeuw","year":"1987","unstructured":"Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Computational and Applied Mathematics, 20, 53\u201365.","journal-title":"Computational and Applied Mathematics"},{"key":"23_CR18","first-page":"583","volume":"3","author":"A. Stehl","year":"2002","unstructured":"Stehl, A., & Gosh, J. (2002). Cluster ensembles\u00a0\u2013 A knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research, 3, 583\u2013618.","journal-title":"Journal of Machine Learning Research"},{"key":"23_CR19","unstructured":"Walesiak, M., & Dudek, A. (2011). The clusterSim package. http:\/\/www.R-project.org\/."}],"container-title":["Studies in Classification, Data Analysis, and Knowledge Organization","Data Analysis, Machine Learning and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-01595-8_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T19:44:09Z","timestamp":1675799049000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-01595-8_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,10,10]]},"ISBN":["9783319015941","9783319015958"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-01595-8_23","relation":{},"ISSN":["1431-8814"],"issn-type":[{"type":"print","value":"1431-8814"}],"subject":[],"published":{"date-parts":[[2013,10,10]]},"assertion":[{"value":"10 October 2013","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}