{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T12:34:12Z","timestamp":1730205252892,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2018,9,1]],"date-time":"2018-09-01T00:00:00Z","timestamp":1535760000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2018,9,1]],"date-time":"2018-09-01T00:00:00Z","timestamp":1535760000000},"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":[[2018,9]]},"DOI":"10.1109\/ceec.2018.8674215","type":"proceedings-article","created":{"date-parts":[[2019,3,29]],"date-time":"2019-03-29T06:21:25Z","timestamp":1553840485000},"page":"248-253","source":"Crossref","is-referenced-by-count":0,"title":["SLDPC: Towards Second Order Learning for Detecting Persistent Clusters in Data Streams"],"prefix":"10.1109","author":[{"given":"Ammar Al Abd","family":"Alazeez","sequence":"first","affiliation":[{"name":"Department of Applied Computing, The University of Buckingham, Buckingham, MK18 1EG, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sabah","family":"Jassim","sequence":"additional","affiliation":[{"name":"Department of Applied Computing, The University of Buckingham, Buckingham, MK18 1EG, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongbo","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Applied Computing, The University of Buckingham, Buckingham, MK18 1EG, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","first-page":"636","article-title":"A Survey: Clustering Ensembles Techniques","volume":"38","author":"ghaemi","year":"2009","journal-title":"Engineering and Technology"},{"journal-title":"Clustering Ensemble Method","year":"2017","author":"alqurashi","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2010.125"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1186\/s12937-017-0226-9"},{"key":"ref14","first-page":"905","article-title":"Stability of Density-Based Clustering","volume":"13","author":"rinaldo","year":"2012","journal-title":"Journal of Machine Learning Research"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1162\/089976604773717621"},{"journal-title":"Clustering Transient Data Streams By Example And By Variable","year":"2009","author":"chaovalit","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2016.2618909"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"1901","DOI":"10.1109\/TNN.2011.2171713","article-title":"Incremental learning from stream data","volume":"22","author":"he","year":"2011","journal-title":"IEEE Trans of Neural Networks"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972764.29"},{"key":"ref4","first-page":"1","article-title":"Clustering Stability: An Overview","author":"luxburg","year":"2010","journal-title":"arXiv 1007 1075v1 now-the essence of knowldge"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/B978-012722442-8\/50016-1"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"173","DOI":"10.5220\/0006196901730183","article-title":"EINCKM: An Enhanced Prototype-based Method for Clustering Evolving Data Streams in Big Data","author":"al abd alazeez","year":"2017","journal-title":"Proceedings of the International Conference on Pattern Recognition Applications and Methods"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICAIS.2009.37"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.09.020"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1016\/j.procs.2017.11.411","article-title":"Research on Data Stream Clustering Based on FCM Algorithm","volume":"122","author":"gao","year":"2017","journal-title":"Scince Direct Elsvier Procedia Computer Science"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.2000.892124"},{"key":"ref1","first-page":"951","article-title":"Clustering Techniques for Streaming Data – A Survey","author":"yogita","year":"2012","journal-title":"3rd IEEE International Advance Computing Conference (IACC)"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICSMC.1990.142183"},{"key":"ref20","first-page":"1","author":"zhao","year":"2001","journal-title":"Technical Report Criterion Functions for Document Clustering Experiments and Analysis"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-014-0808-1"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/2522968.2522981"}],"event":{"name":"2018 10th Computer Science and Electronic Engineering (CEEC)","start":{"date-parts":[[2018,9,19]]},"location":"Colchester, UK","end":{"date-parts":[[2018,9,21]]}},"container-title":["2018 10th Computer Science and Electronic Engineering (CEEC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8672424\/8674179\/08674215.pdf?arnumber=8674215","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T19:45:54Z","timestamp":1663098354000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8674215\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/ceec.2018.8674215","relation":{},"subject":[],"published":{"date-parts":[[2018,9]]}}}