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AusDM 2021 : The 19th Australasian Data Mining Conference 2021

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Conference Series : Australasian Data Mining Conference
 
Link: https://ausdm21.ausdm.org/
 
When Dec 13, 2021 - Dec 15, 2021
Where Brisbane, Australia
Submission Deadline Aug 24, 2021
Notification Due Sep 30, 2021
Final Version Due Oct 15, 2021
Categories    datamining   machine learning   deep learning   knowledge management
 

Call For Papers

The 19th Australasian Data Mining Conference (AusDM’21)
Brisbane, Australia, 13-15 December 2021
https://ausdm21.ausdm.org/

The conference is planned to hold in-person in Brisbane. Participants from Australia and New Zealand are encouraged to attend it personally. There will be an option for overseas participants to attend it virtually.

The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. It is devoted to the art and science of intelligent analysis of (usually big) data sets for meaningful (and previously unknown) insights. This conference will enable the sharing and learning of research and progress in the local context and breakthroughs in data mining algorithms and their applications across all industries.

Since AusDM’02 the conference has showcased research in data mining, providing a forum for presenting and discussing the latest research and developments. Built on this tradition, AusDM’21 will facilitate the cross-disciplinary exchange of ideas, experience and potential research directions. Specifically, the conference seeks to showcase: Research Prototypes; Industry Case Studies; Practical Analytics Technology; and Research Student Projects. AusDM’21 will be a meeting place for pushing forward the frontiers of data mining in academia and industry.

Publication and topics
----------------------
We are calling for papers, both research and applications, and from both academia and industry, for publication and presentation at the conference. All papers will go through double-blind, peer–review by a panel of international experts. The AusDM’21 proceeding will be published by Springer-Verlag and become available immediately after the conference.

Please note that AusDM’21 requires that at least one author for each accepted paper register for the conference and present their work.

AusDM’21 invites contributions addressing current research in data mining and knowledge discovery as well as experiences, novel applications and future challenges. Topics of interest include, but are not restricted to:

• Applications and Case Studies
• Big Data Analytics
• Biomedical and Health Data Mining
• Business Analytics
• Computational Aspects of Data Mining
• Data Integration, Matching and Linkage
• Data Mining in Education
• Data Mining in Security and Surveillance
• Data Preparation, Cleaning and Preprocessing
• Data Stream Mining
• Deep Learning
• Evaluation of Results and their Communication
• Implementations of Data Mining in Industry
• Integrating Domain Knowledge
• Link, Tree, Graph, Network and Process Mining
• Machine Learning
• Multimedia Data Mining
• New Data Mining Algorithms
• Professional Challenges in Data Mining
• Privacy-preserving Data Mining
• Spatial and Temporal Data Mining
• Text Mining
• Visual Analytics
• Web and Social Network Mining

Keynote speakers
----------------
As is tradition for AusDM we have lined up an excellent keynote speaker program. Each speaker is a well-known research and/or practitioner in data mining and related disciplines. The keynote program provides an opportunity to hear from some of the world’s leaders on what the technology offers and where it is heading.

Submission of papers
--------------------
We invite three types of submissions for AusDM’21:
• Research Track: Academic submissions reporting on new algorithms, novel approaches and research progress, with a paper length of maximum 16 pages in Springer style, as detailed below.
• Application Track: Submissions reporting on applications of data mining and machine learning and describing specific data mining implementations and experiences in the real world. Submissions in this category can be of a maximum length of 16 pages in Springer style.
• Industry Showcase Track: Submissions from governments and industry on an analytics solution that has raised profits, reduced costs and/or achieved other important policy and/or business outcomes can be made in this track. There will be an option of full paper submission with a maximum paper length of 10 pages in Springer style or an extended abstract.

All submissions will go through a double-blind review process, i.e. paper submissions must NOT include authors names or affiliations or acknowledgments referring to funding bodies. Self-citing references should also be removed from the submitted papers for the double-blinded reviewing purpose. The information can be added in the accepted final camera-ready submissions.

Important Dates
---------------
Paper submissions: 7 Sept 2021
Notification: 30 September 2021
Camera-ready: 15 October 2021
Conference: 13-15 December 2021

Organising Committee
====================

Conference Chairs
-----------------
Richi Nayak, Queensland University of Technology
Yanchang Zhao, Data61, CSIRO
Graham Williams, The Australian National University

Research and Application Track Program Chairs
---------------------------------------------
Yue Xu, Queensland University of Technology
Rosalind Wang, Western Sydney
Anton Lord, Leap In!

Industry Track Program Chairs
-----------------------------
Annette Slunjski, IAPA
Warwick Graco, ATO

Organising Chairs
-----------------
Khanh Luong, Queensland University of Technology
Thirunavukarasu Balasubramanium, Queensland University of Technology

Publicity Chair
---------------
Md Abul Bashar, Queensland University of Technology

Publication Chair
-----------------
Yee Ling Boo, RMIT University

Steering Committee
------------------
Simeon Simoff (Chair), University of Western Sydney
Graham Williams (Chair), The Australian National University
Peter Christen, The Australian National University
Ling Chen, University of Technology
Zahid Islam, Charles Sturt University
Paul Kennedy, University of Technology
Yun Sing Koh, The University of Auckland
Jiuyong (John) Li, University of South Australia
Richi Nayak, Queensland University of Technology
Kok–Leong Ong, La Trobe University
Dharmendra Sharma, University of Canberra
Glenn Stone, Western Sydney University Yanchang Zhao, Data61, CSIRO

Further Information
-------------------
AusDM’21 website: https://ausdm21.ausdm.org/
Contact the organisers of AusDM’21 at ausdm21@ausdm.org
AusDM LinkedIn Group: https://www.linkedin.com/groups/4907891/

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