{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:56:24Z","timestamp":1761598584933,"version":"3.37.3"},"reference-count":31,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Digital Europe Grant Testing and Experimentation Facility for Health Artificial Intelligence (AI) and Robotics","award":["101100700"],"award-info":[{"award-number":["101100700"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3507133","type":"journal-article","created":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T19:41:56Z","timestamp":1732736516000},"page":"179879-179890","source":"Crossref","is-referenced-by-count":1,"title":["The Impact of Random Models on Standardized Clustering Similarity"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1284-541X","authenticated-orcid":false,"given":"Kai","family":"Klede","sequence":"first","affiliation":[{"name":"Machine Learning and Data Analytics (MaD) Laboratory, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2326-4258","authenticated-orcid":false,"given":"Thomas R.","family":"Altstidl","sequence":"additional","affiliation":[{"name":"Machine Learning and Data Analytics (MaD) Laboratory, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5886-0597","authenticated-orcid":false,"given":"Dario","family":"Zanca","sequence":"additional","affiliation":[{"name":"Machine Learning and Data Analytics (MaD) Laboratory, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0417-0336","authenticated-orcid":false,"given":"Bj\u00f6rn M.","family":"Eskofier","sequence":"additional","affiliation":[{"name":"Machine Learning and Data Analytics (MaD) Laboratory, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"16904","DOI":"10.1109\/ACCESS.2017.2741221","article-title":"Generalized pair-counting similarity measures for clustering and cluster ensembles","volume":"5","author":"Zhang","year":"2017","journal-title":"IEEE Access"},{"key":"ref2","doi-asserted-by":"crossref","DOI":"10.1201\/b15410","volume-title":"Data Clustering Algorithms and Applications","author":"Aggarwal","year":"2013"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"42740","DOI":"10.1109\/ACCESS.2018.2852648","article-title":"Revisiting K-means and topic modeling, a comparison study to cluster Arabic documents","volume":"6","author":"Alhawarat","year":"2018","journal-title":"IEEE Access"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"44097","DOI":"10.1109\/ACCESS.2019.2908718","article-title":"Multilevel thresholding segmentation for color image using modified moth-flame optimization","volume":"7","author":"Jia","year":"2019","journal-title":"IEEE Access"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"126481","DOI":"10.1109\/ACCESS.2021.3109168","article-title":"A comprehensive unsupervised framework for chronic kidney disease prediction","volume":"9","author":"Antony","year":"2021","journal-title":"IEEE Access"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/icdm.2010.85"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/BigDIA53151.2021.9619704"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3137396"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2021.3104155"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.5555\/1756006.1953024"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1971.10482356"},{"key":"ref12","first-page":"1073","article-title":"Information theoretic measures for clusterings comparison: Is a correction for chance necessary?","volume-title":"Proc. 26th Annu. Int. Conf. Mach. Learn. (ICML)","volume":"382","author":"Nguyen"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.12.003"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/bf01908075"},{"key":"ref15","first-page":"1143","article-title":"Standardized mutual information for clustering comparisons: One step further in adjustment for chance","volume-title":"Proc. 31st Int. Conf. Mach. Learn.","author":"Romano"},{"issue":"134","key":"ref16","first-page":"1","article-title":"Adjusting for chance clustering comparison measures","volume":"17","author":"Romano","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"ref17","first-page":"27113","article-title":"p-value adjustment for monotonous, unbiased, and fast clustering comparison","volume-title":"Proc. Adv. Neural Inf. Process. Syst. 36 (NeurIPS)","volume":"36","author":"Klede"},{"key":"ref18","first-page":"1","article-title":"The impact of random models on clustering similarity","volume":"18","author":"Gates","year":"2017","journal-title":"J. Mach. Learn. Res."},{"key":"ref19","first-page":"281","article-title":"Some methods for classification and analysis of multivariate observations","volume-title":"Proc. 5th Berkeley Symp. Math. Statist. Probab.","volume":"1","author":"MacQueen"},{"issue":"34","key":"ref20","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"96","author":"Ester","year":"1996","journal-title":"Proc. KDD"},{"key":"ref21","first-page":"3799","article-title":"Systematic analysis of cluster similarity indices: How to validate validation measures","volume-title":"Proc. 38th Int. Conf. Mach. Learn. (ICML)","volume":"139","author":"G\u00f6sgens"},{"volume-title":"Concrete Mathematics","year":"1988","author":"Graham","key":"ref22"},{"issue":"3","key":"ref23","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.spl.2004.06.009","article-title":"Moments of rand\u2019s c statistic in cluster analysis","volume":"69","author":"DuBien","year":"2004","journal-title":"Statist. Probab. Lett."},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-4072-3_4"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i7.26003"},{"key":"ref26","article-title":"Pairwise adjusted mutual information","author":"Lazarenko","year":"2021","journal-title":"arXiv:2103.12641"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.2307\/2346669"},{"key":"ref28","first-page":"357","article-title":"The complexity of nonuniform random number generation","volume-title":"Proc. Symp. New Directions Recent Results Algorithms Complexity","author":"Knuth"},{"key":"ref29","article-title":"Probabilistic divide-and-conquer: A new exact simulation method, with integer partitions as an example","author":"Arratia","year":"2011","journal-title":"arXiv:1110.3856"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s00180-019-00899-7"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-9-497"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10380310\/10769363.pdf?arnumber=10769363","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T02:02:34Z","timestamp":1733882554000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10769363\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3507133","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2024]]}}}