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 new 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’20 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’20 will be a meeting place for pushing forward the frontiers of data mining in academia and industry. In this year, AusDM is pleased to be co-located with the 2020 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2020) in Canberra, Australia. The IEEE SSCI co-locates several symposia under one roof, each dedicated to a specific topic in the Computational Intelligence domain.

AusDM 2020 GOES VIRTUAL
The Australasian Data Mining Conference is 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.

AusDM’20 takes the safety and health of its attendees to heart. After studying and evaluating the current COVID19 epidemic, the Organizing Committee has decided that AusDM’20 will be run as a fully virtual conference on 1 - 4 December 2020.

Be Safe, Be Healthy, and Be Ready to submit your best work to AusDM’20 on time.


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 2020 proceeding will be published by IEEE and become available immediately after the conference.

Please note that AusDM’20 requires that at least one author for each accepted paper register for the conference and present their work.

AusDM 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 — Lessons and Experiences
• 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
• Evaluation of Results and their Communication

• Implementations of Data Mining in Industry
• Integrating Domain Knowledge
• Link, Tree, Graph, Network and Process Mining
• 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
AusDM’20 will feature three types of papers

Research Track: Submissions reporting on new algorithms, novel approaches, research progress of data mining and machine learning.

Application Track: Submissions on specific data mining implementations and experiences in government and industry settings, applications of data mining and machine learning in the real world.

Submissions in these two categories will be reviewed using the IEEE SSCI paper management system, with accepted papers appearing in the IEEE SSCI 2020 proceedings. Instructions for authors are the same as other IEEE SSCI 2020 papers.

Industry Showcase Track: Submissions from governments and industry on innovative applications of data mining and analytics solutions that have improved the quality of data products and have raised profits, reduced costs and/or achieved other important policy and/or business outcomes can be made in this track. Participants can either submit an extended abstract to be included in the conference program or a full paper to submit in the application track for peer-reviewed publication. Extended abstract can be submitted to ausdm20@ausdm.org directly and will be handled independently and will appear on the AusDM2020 website.


Important Dates
Submissions: 7 August 2020 (no extension)
Notification: 4 September 2020
Camera-ready: 18 September 2020
Conference: 1-4 December 2019


Organising Committee
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Conference Chairs
• Rohan Baxter, Australian Taxation Office
• Richi Nayak, Queensland University of Technology
• Dharmendra Sharma, University of Canberra

Program Chairs – Research Track
• Mohammad Abualsheikh, University of Canberra
• Yue Xu, Queensland University of Technology

Program Chairs – Applications Track
• Yanchang Zhao, Data61, CSIRO
• Dat Tran, University of Canberra

Program Chairs – Industry Showcase Track
• Jin Li, Data2Action
• Alex Antic, The Australian National University

Publicity Chair
• Md Abul Bashar, Queensland University of Technology

Steering Committee
• Simeon Simoff (Chair), University of Western Sydney
• Graham William (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
• Yanchang Zhao, Data61, CSIRO
• Lin Liu, University of South Australia

Further Information

AusDM’20 website: https://ausdm20.ausdm.org/

Contact the organisers of AusDM 2020 at ausdm20@ausdm.org AusDM

LinkedIn Group: https://www.linkedin.com/groups/4907891/

AusDM'20 Facebook Page: https://www.facebook.com/ausdm2020

AusDM'20 Twitter: https://twitter.com/ausdm2020