pakdd16.wordpress.fos.auckland.ac.nz
Important Dates – PAKDD 2016
http://pakdd16.wordpress.fos.auckland.ac.nz/calls/important-dates
Pacific Asia Knowledge Discovery and Data Mining Conference (PAKDD) 2016. Paper submission due: October 4, 2015 October 8, 2015 [23:59:59 Pacific Time] (Extended deadline). Notification to authors: December 11, 2015. Camera ready papers due: January 15, 2016. Conference dates: April 19-22, 2016. Workshop proposal due: September 28, 2015 [23:23:59 PST]. Workshop notification: October 2, 2015. Workshop call for papers: October 16, 2015. Suggested workshop author notification: January 22, 2016.
pakdd16.wordpress.fos.auckland.ac.nz
Program Committee – PAKDD 2016
http://pakdd16.wordpress.fos.auckland.ac.nz/organization/program-committee
Pacific Asia Knowledge Discovery and Data Mining Conference (PAKDD) 2016. Senior Program Committee Members:. Michael Berthold, University of Konstanz, Germany. Tru Cao, Ho Chi Minh City University of Technology, Vietnam. Ming-Syan Chen, National Taiwan University, Taiwan. Peter Christen, The Australian National University, Australia. Ian Davidson, UC Davis, USA. Guozhu Dong, Wright State University. Bart Goethals, University of Antwerp, Belgium. Xiaohua Hu, Drexel University, USA. Dou Shen, Baidu, China.
pakdd16.wordpress.fos.auckland.ac.nz
Submission Site – PAKDD 2016
http://pakdd16.wordpress.fos.auckland.ac.nz/paper-submission/submission-site
Pacific Asia Knowledge Discovery and Data Mining Conference (PAKDD) 2016. Please visit https:/ cmt.research. And create an account to submit your paper. Website created by Alexandr Shirokov Developed and maintained by David TJ Huang. Department of Computer Science. The University of Auckland.
pakdd16.wordpress.fos.auckland.ac.nz
Call for Contests – PAKDD 2016
http://pakdd16.wordpress.fos.auckland.ac.nz/calls/call-for-contests
Pacific Asia Knowledge Discovery and Data Mining Conference (PAKDD) 2016. We invite proposals for organizers of the PAKDD 2016 Data Mining Contest. The Data Mining Contest is an integral part of the conference and provides an opportunity for teams of scientists and domain experts to compete in order to develop data mining techniques for real-world applications. Proposals should contain the following information:. Contest title and abstract. General description of the problem. Website created by Alexandr ...
pakdd16.wordpress.fos.auckland.ac.nz
Organizers – PAKDD 2016
http://pakdd16.wordpress.fos.auckland.ac.nz/organization/organizers
Pacific Asia Knowledge Discovery and Data Mining Conference (PAKDD) 2016. Department of Computer Science. The University of Auckland. School of Computer and Mathematical Science. School of Engineering and Advanced Technology. Website created by Alexandr Shirokov Developed and maintained by David TJ Huang. Department of Computer Science. The University of Auckland.
pakdd16.wordpress.fos.auckland.ac.nz
Workshops – PAKDD 2016
http://pakdd16.wordpress.fos.auckland.ac.nz/technical-program/workshops
Pacific Asia Knowledge Discovery and Data Mining Conference (PAKDD) 2016. The workshop papers will be published as joint post-proceedings in the LNAI series. Workshop Title: 5th PAKDD Workshop on Biologically Inspired Data Mining Techniques. Workshop URL: https:/ conference.fos.auckland.ac.nz/bdm/bdm16/. Shafiq Alam, University of Auckland, New Zealand. Gillian Dobbie, University of Auckland, New Zealand. Gill@cs.auckland.ac.nz. Workshop Title: Machine Learning for Sensory Data Analysis. Ling Liu, Southw...
pakdd16.wordpress.fos.auckland.ac.nz
Call for Papers – PAKDD 2016
http://pakdd16.wordpress.fos.auckland.ac.nz/calls/call-for-papers
Pacific Asia Knowledge Discovery and Data Mining Conference (PAKDD) 2016. The 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining. April 19-22, 2016, Auckland, New Zealand. Http:/ pakdd2016.pakdd.org/. Paper submission due: October 4, 2015 October 8, 2015 [23:59:59 Pacific Time] (Extended deadline). Notification to author: December 11, 2015. Camera ready due: January 15, 2016. Conference: April 19-22, 2016. Novel models and algorithms. Statistical methods for data mining. The submitted pa...
SOCIAL ENGAGEMENT