Exceptional contrast set mining: moving beyond the deluge of the obvious Nguyen, Dang, Luo, Wei, Phung, Dinh and Venkatesh, Svetha 2016, Exceptional contrast set mining: moving beyond the deluge of the obvious, in AI 2016 : Advances in artificial intelligence : Proceedings of the 29th Australian Joint Conference, Springer International, Cham, Switzerland, pp. 455-468, doi: 10.1007/978-3-319-50127-7_39. Attached Files Name Description MIMEType Size Downloads Title Exceptional contrast set mining: moving beyond the deluge of the obvious Author(s) Nguyen, Dang orcid.org/0000-0002-0401-988X Luo, Wei orcid.org/0000-0002-4711-7543 Phung, Dinh orcid.org/0000-0002-9977-8247 Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Conference name Australian Computer Society for AI. Conference (29th : 2016 : Hobart, Tasmania) Conference location Hobart, Tas. Conference dates 2016/12/05 - 2016/12/08 Title of proceedings AI 2016 : Advances in artificial intelligence : Proceedings of the 29th Australian Joint Conference Editor(s) Ho Kang, Byeong Bai, Quan Publication date 2016 Series Australian Computer Society for AI Conference Start page 455 End page 468 Total pages 14 Publisher Springer International Place of publication Cham, Switzerland Keyword(s) exceptional contrast set mining affirmative contrast sets exceptional contrast sets algorithm data ISBN 9783319501260 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-319-50127-7_39 HERDC Research category E1 Full written paper - refereed ERA Research output type E Conference publication Copyright notice ©2016, Springer International Publishing AG Persistent URL http://hdl.handle.net/10536/DRO/DU:30093558 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment Centre for Pattern Recognition and Data Analytics (PRADA) Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 06 Apr 2017, 12:03:38 EST Fri, 07 Apr 2017, 05:04:31 EST Fri, 15 Sep 2017, 17:51:10 EST Sat, 16 Sep 2017, 06:02:41 EST Mon, 18 Sep 2017, 13:06:00 EST Mon, 18 Sep 2017, 13:08:57 EST Mon, 18 Sep 2017, 13:09:48 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 430 Abstract Views, 7 File Downloads  -  Detailed Statistics Created: Fri, 15 Sep 2017, 17:51:10 EST

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