Fast community detection with graph sparsification Laeuchli, Jesse 2020, Fast community detection with graph sparsification, in PAKDD 2020 : Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, Cham, Switzerland, pp. 291-304, doi: 10.1007/978-3-030-47426-3_23. Attached Files Name Description MIMEType Size Downloads Title Fast community detection with graph sparsification Author(s) Laeuchli, Jesse orcid.org/0000-0001-9970-9105 Conference name Knowledge Discovery and Data Mining. Conference (24th : 2020 : Singapore) Conference location Singapore Conference dates 2020/05/11 - 2020/05/14 Title of proceedings PAKDD 2020 : Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining Editor(s) Lauw, Hady W Chi-Wing Wong, Raymond Ntoulas, Alexandros Lim, Ee-Peng Ng, See-Kiong Pan, Sinno Jialin Publication date 2020 Series Knowledge Discovery and Data Mining Conference Start page 291 End page 304 Total pages 14 Publisher Springer Place of publication Cham, Switzerland Keyword(s) clustering graph sparsification stopping criteria ISBN 9783030474256 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-030-47426-3_23 Indigenous content off Field of Research 08 Information and Computing Sciences HERDC Research category E1 Full written paper - refereed Free to Read? Yes Free to Read Start Date 2021-06-01 Persistent URL http://hdl.handle.net/10536/DRO/DU:30137117 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Link to full-text (open access)   Connect to published version (restricted access) Go to link with your DU access privileges   Connect to Elements publication management system 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. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Fri, 15 May 2020, 22:17:51 EST Sat, 16 May 2020, 05:02:08 EST Mon, 18 May 2020, 08:51:42 EST Tue, 19 May 2020, 06:07:16 EST Thu, 21 May 2020, 12:50:38 EST Thu, 21 May 2020, 12:57:29 EST Thu, 21 May 2020, 12:58:04 EST Thu, 21 May 2020, 13:01:33 EST Thu, 21 May 2020, 14:01:01 EST Thu, 28 May 2020, 14:51:15 EST Wed, 08 Jul 2020, 09:25:13 EST Wed, 08 Jul 2020, 09:26:49 EST Wed, 08 Jul 2020, 09:27:28 EST Mon, 13 Jul 2020, 16:36:01 EST Sat, 04 Dec 2021, 01:32:33 EST Filtered Full Citation counts:   Cited 3 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 226 Abstract Views, 13 File Downloads  -  Detailed Statistics Created: Mon, 18 May 2020, 08:51:42 EST