{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T12:26:23Z","timestamp":1744892783603,"version":"3.28.0"},"reference-count":27,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,8]]},"DOI":"10.1109\/iri.2013.6642535","type":"proceedings-article","created":{"date-parts":[[2013,10,31]],"date-time":"2013-10-31T00:13:22Z","timestamp":1383178402000},"page":"692-699","source":"Crossref","is-referenced-by-count":4,"title":["MFWK-Means: Minkowski metric Fuzzy Weighted K-Means for high dimensional data clustering"],"prefix":"10.1109","author":[{"given":"L.","family":"Svetlova","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B.","family":"Mirkin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"H.","family":"Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"19","first-page":"89","article-title":"Fuzzy possibility c-meanbased on complete mahalanobis distance and separablecriterion","author":"liu","year":"2008","journal-title":"Eighth International Conference on IntelligentSystems Design and Applications"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1109\/91.227387"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZY.1997.616338"},{"key":"15","article-title":"Smeans: Similarity driven clustering and its application ingravitational-wave astronomy data mining","author":"lei","year":"2007","journal-title":"Proceedings of TheInt Workshop on Knowledge Discovery from Ubiquitous DataStreams (IWKDUDS 2007)"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1007\/s00357-010-9049-5"},{"key":"13","first-page":"727","author":"pelleg","year":"2000","journal-title":"Xmeans Extending Kmeans WithSeventeenth International Conference on Machine Learning"},{"key":"14","volume":"17","author":"hamerly","year":"2003","journal-title":"Learning the K in K-means Advances in Neural Information Processing Systems"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.95"},{"key":"12","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1016\/j.patcog.2011.08.012","article-title":"Minkowski metric, feature weighting and anomalous cluster initializing in kmeansclustering","volume":"45","author":"de a r cordeiro","year":"2012","journal-title":"Pattern Recognition"},{"key":"21","article-title":"Laplaciannormalization for deriving semantic fuzzy clusters with anadditive spectral approach","author":"nascimento","year":"2012","journal-title":"Expert Systems"},{"key":"20","first-page":"90","article-title":"Fuzzy c-mean algorithm withmorphology similarity distance","volume":"3","author":"li","year":"2009","journal-title":"Proceedings of the SixthInternational Conference on Fuzzy Systems and KnowledgeDiscovery"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/0031-3203(94)90119-8"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2009.06.018"},{"journal-title":"UCI Machine LearningRepository","year":"2007","author":"asuncion","key":"24"},{"journal-title":"Bisecting K-Means and 1DProjection Divisive Clustering A Unified Framework Andexperimental Comparisons","year":"0","author":"kovaleva","key":"25"},{"key":"26","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/978-3-540-73560-1_15","article-title":"Clustering methods: A history of K-meansalgorithms","author":"bock","year":"2007","journal-title":"Selected Contributions in Data Analysis AndClassification"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1348\/000711005X48266"},{"journal-title":"A K-means Clustering Algorithm YaleUniversity","year":"1979","author":"hartigan","key":"3"},{"key":"2","first-page":"342","author":"kaufman","year":"1990","journal-title":"Finding groups in data Anintroduction to cluster analysis"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2003.11.003"},{"key":"1","doi-asserted-by":"crossref","DOI":"10.1201\/b13101","author":"mirkin","year":"2012","journal-title":"Clustering A Data Recovery Approach Chapman and Hall\/CRC"},{"key":"7","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1007\/s00357-001-0018-x","article-title":"Optimal variable weighting forultrametric and additive trees and K-Means partitioning","volume":"18","author":"makarenkov","year":"2001","journal-title":"Journalof Classification"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1007\/BF01901677"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2009.09.011"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-0450-1"},{"key":"9","first-page":"193","article-title":"Weighting method forfeature selection in k-means","author":"huang","year":"2008","journal-title":"Computational Methods of Feature Selection"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687770"}],"event":{"name":"2013 IEEE 14th International Conference on Information Reuse & Integration (IRI)","start":{"date-parts":[[2013,8,14]]},"location":"San Francisco, CA, USA","end":{"date-parts":[[2013,8,16]]}},"container-title":["2013 IEEE 14th International Conference on Information Reuse & Integration (IRI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6621630\/6642428\/06642535.pdf?arnumber=6642535","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,7]],"date-time":"2020-08-07T03:54:28Z","timestamp":1596772468000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/6642535\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,8]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/iri.2013.6642535","relation":{},"subject":[],"published":{"date-parts":[[2013,8]]}}}