{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T23:06:54Z","timestamp":1729638414178,"version":"3.28.0"},"reference-count":35,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,10]]},"DOI":"10.1109\/bigdata.2013.6691749","type":"proceedings-article","created":{"date-parts":[[2014,1,3]],"date-time":"2014-01-03T19:11:49Z","timestamp":1388776309000},"page":"161-168","source":"Crossref","is-referenced-by-count":6,"title":["Scalable approximation of kernel fuzzy c-means"],"prefix":"10.1109","author":[{"given":"Zijian","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Timothy C.","family":"Havens","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"19","doi-asserted-by":"publisher","DOI":"10.1145\/360402.360419"},{"key":"35","doi-asserted-by":"publisher","DOI":"10.1007\/BF01908075"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1016\/0020-0255(94)00111-N"},{"key":"18","first-page":"51","article-title":"Scaling clustering algorithms to large databases","author":"bradley","year":"2000","journal-title":"The Fourth International Conference on Knowledge Discovery and Data Mining"},{"key":"33","first-page":"2153","article-title":"On the nystrom method for approximating a gram matrix for improved kernel-based learning","volume":"6","author":"drineas","year":"2005","journal-title":"J Machine Learning Research"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020558"},{"key":"34","article-title":"Improved bounds for the nystrom method with application to kernel classification","author":"jin","year":"2013","journal-title":"IEEE Trans Info Theory"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1145\/130226.134466"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1002\/int.20162"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1002\/int.20268"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1145\/312129.312188"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2006.02.008"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1109\/ICSMC.2006.384634"},{"key":"20","article-title":"Genic: A single pass generalized incremental algorithm for clustering","author":"gupta","year":"2004","journal-title":"SIAM Int Conf on Data Mining"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2003.1198387"},{"key":"23","article-title":"Streaming k-means approximation","author":"ailon","year":"2009","journal-title":"NIPS"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.14778\/2180912.2180915"},{"key":"25","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1145\/235968.233324","article-title":"Birch: An efficient data clustering method for very large databases","author":"zhang","year":"1996","journal-title":"ACM SIGMOD Int Conf Manag Data"},{"journal-title":"Finding Groups in Data An Introduction to Cluster Analysis","year":"1990","author":"kaufman","key":"26"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2002.1033770"},{"key":"28","first-page":"3","volume":"399","author":"havens","year":"2012","journal-title":"Computational Intelligence Revised and Selected Papers from IJCCI 2010"},{"key":"29","first-page":"49","article-title":"Fuzzy c-means clustering algorithm based on kernel method","author":"wu","year":"2003","journal-title":"Proc Int Conf Computational Intelligence and Multimedia Applications"},{"key":"3","article-title":"Single pass fuzzy c means","author":"hore","year":"2007","journal-title":"Fuzzy Systems Conferences"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511809682.002"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2002.1033179"},{"key":"1","first-page":"501","article-title":"Clustering large datasets with kernel methods","author":"fausser","year":"2012","journal-title":"Proc Int Conf Pattern Recognition"},{"key":"30","doi-asserted-by":"publisher","DOI":"10.1016\/0031-3203(89)90066-6"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2012.2201485"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2003.809902"},{"key":"32","article-title":"Approximation of kernel k means for streaming data","author":"havens","year":"2012","journal-title":"21st International Conference on Pattern Recognition"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/ICSMC.2007.4413710"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZY.2005.1452429"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1109\/NAFIPS.2007.383888"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/NAFIPS.2008.4531233"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZY.2011.6007618"}],"event":{"name":"2013 IEEE International Conference on Big Data","start":{"date-parts":[[2013,10,6]]},"location":"Silicon Valley, CA, USA","end":{"date-parts":[[2013,10,9]]}},"container-title":["2013 IEEE International Conference on Big Data"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6679357\/6690588\/06691749.pdf?arnumber=6691749","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,22]],"date-time":"2017-06-22T05:15:11Z","timestamp":1498108511000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/6691749\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,10]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/bigdata.2013.6691749","relation":{},"subject":[],"published":{"date-parts":[[2013,10]]}}}