A distance scaling method to improve density-based clustering Zhu, Ye, Ting, Kai Ming and Angelova, Maia 2018, A distance scaling method to improve density-based clustering, in PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference, Springer, Cham, Switzerland, pp. 389-400, doi: 10.1007/978-3-319-93040-4_31. Attached Files Name Description MIMEType Size Downloads Title A distance scaling method to improve density-based clustering Author(s) Zhu, Ye orcid.org/0000-0003-4776-4932 Ting, Kai Ming Angelova, Maia orcid.org/0000-0002-0931-0916 Conference name Knowledge Discovery and Data Mining. Pacific-Asia Conference (22nd : 2018 : Melbourne, Victoria) Conference location Melbourne, Victoria Conference dates 2018/06/03 - 2018/06/06 Title of proceedings PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference Editor(s) Phung, D Tseng, V Webb, G Ho, B Ganji, M Rashidi, LR Publication date 2018 Series Lecture Notes in Computer Science Start page 389 End page 400 Total pages 12 Publisher Springer Place of publication Cham, Switzerland ISBN 9783319930398 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-319-93040-4_31 Field of Research 08 Information And Computing Sciences HERDC Research category E1 Full written paper - refereed ERA Research output type E Conference publication Persistent URL http://hdl.handle.net/10536/DRO/DU:30112479 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology 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 Tue, 14 Aug 2018, 21:03:30 EST Wed, 15 Aug 2018, 05:02:08 EST Wed, 15 Aug 2018, 08:05:13 EST Wed, 27 Feb 2019, 05:01:59 EST Wed, 27 Feb 2019, 13:14:42 EST Wed, 27 Feb 2019, 13:17:04 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 5 times in Scopus Search Google Scholar Access Statistics: 203 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Tue, 14 Aug 2018, 21:03:30 EST

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