AusDM'20: The 18th Australasian Data Mining Conference 2020

Country: Australia

City: Canberra

Abstr. due: 07.08.2020

Dates: 01.12.20 — 04.12.20

Area Of Sciences: Physics and math; Technical sciences;

Organizing comittee e-mail: ausdm20 AT

Organizers: IEEE


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.

List of 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

Conference Web-Site: