{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T10:12:57Z","timestamp":1775470377870,"version":"3.50.1"},"reference-count":30,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T00:00:00Z","timestamp":1653436800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T00:00:00Z","timestamp":1653436800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,25]]},"DOI":"10.1109\/eais51927.2022.9787746","type":"proceedings-article","created":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T20:23:35Z","timestamp":1654547015000},"page":"1-5","source":"Crossref","is-referenced-by-count":3,"title":["Evolving clustering algorithm based on average cluster distance - eCAD"],"prefix":"10.1109","author":[{"given":"Goran","family":"Andonovski","sequence":"first","affiliation":[{"name":"University of Ljubljana,Faculty of Electrical Engineering,Ljubljana,Slovenia"}]},{"given":"Igor","family":"Skrjanc","sequence":"additional","affiliation":[{"name":"University of Ljubljana,Faculty of Electrical Engineering,Ljubljana,Slovenia"}]}],"member":"263","reference":[{"key":"ref30","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3037240"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2628722"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3006069"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.227"},{"key":"ref14","first-page":"281","article-title":"Some methods for classification and analysis of multivariate observations","author":"macqueen","year":"1967","journal-title":"5-th Berkeley Symposium on Mathematical Statistics and Probability"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-0450-1"},{"key":"ref16","first-page":"455","article-title":"Clustering with decision trees: Divisive and agglomerative approach","author":"castin","year":"2018","journal-title":"ESANN 2018 - Proceedings European Symposium on Artificial Neural Networks Computational Intelligence and Machine Learning"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2008.4761261"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.03.060"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s12530-020-09334-5"},{"key":"ref28","first-page":"318","article-title":"Improving the cluster structure extracted from OPTICS plots","volume":"2191","author":"schubert","year":"2018","journal-title":"Proc of the Conference “Lernen Wissen Daten Analysen” (LWDA) (2018)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2012.2223679"},{"key":"ref27","first-page":"226","article-title":"A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise","author":"ester","year":"1996","journal-title":"Proc of the Second Int Conf on Knowledge Discovery and Data Mining"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/GRC.2014.6982800"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.251"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-1238-7"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2019.2956973"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2014.2306840"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2040763"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2855437"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1109\/TCBB.2014.2359433","article-title":"Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data","volume":"12","author":"yu","year":"2015","journal-title":"IEEE\/ACM Transactions on Computational Biology and Bioinformatics"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2014.2330519"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-1794-2"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2019.2931874"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/EAIS.2016.7502508"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.12.004"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/EAIS.2017.7954834"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.14313\/JAMRIS_2-2014\/16"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.01.017"}],"event":{"name":"2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)","location":"Larnaca, Cyprus","start":{"date-parts":[[2022,5,25]]},"end":{"date-parts":[[2022,5,26]]}},"container-title":["2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9787685\/9787686\/09787746.pdf?arnumber=9787746","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,11]],"date-time":"2022-07-11T20:00:30Z","timestamp":1657569630000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9787746\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,25]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/eais51927.2022.9787746","relation":{},"subject":[],"published":{"date-parts":[[2022,5,25]]}}}