************************************************************
** Call for Papers **
** The 17th Australasian Data Mining Conference (AusDM’19) **
** Adelaide, Australia, 2-5 December 2019 **
*************************************************************

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’19 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’19 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 Australasian Joint Conference on Artificial Intelligence (AI’19) in Adelaide, Australia.

**Publication and topics
We are calling for papers, both research and applications, and from both academia and industry, for presentation at the conference. All papers will go through double–blind, peer–review by a panel of international experts. Since 2017, all AusDM proceedings have been published in Springers Communication in Computer and Information Science (CCIS). CCIS is abstracted/indexed in DBLP, Google Scholar, EI-Compendex, Mathematical Reviews, SCImago, Scopus. Previous AusDM proceedings (2006 to 2016) have been published as volumes in the Conferences in Research and Practice in Information Technology (CRPIT) series.

Please note that AusDM’19 requires that at least one author for each accepted paper register for the conference and present their work, and one registration covers only one paper.

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
We invite three types of submissions for AusDM’19:
- Research Track: Academic submissions reporting on new algorithms, novel approaches and research progress, with a paper length of between 8 and 12 pages in CCIS 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 between 6 and 12 pages in CCIS 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 with a paper length between 4 and 6 pages in CCIS style.

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.

All submissions are required to follow the format specified for papers in the CCIS style. Author guideline, LaTeX style file and Word template of the CCIS style can be found on AusDM’19 Submission Page (https://ausdm19.ausdm.org/submission.php). The electronic submissions must be in PDF only and made through the AusDM’19 Submission Page.

**Important Dates
Paper submission (extended dealine): 12 August 2019*
Notification: 30 September 2019
Camera-ready: 14 October 2019*
Conference: 2-5 December 2019
(*Anywhere on Earth Time)

**Organising Committee
- Conference Chairs
Lin Liu, University of South Australia
Graham William, Microsoft

- Program Chairs
Thuc Le, University of South Australia
Kok–Leong Ong, La Trobe University
Yanchang Zhao, Data61, CSIRO
Warren Jin, Data61, CSIRO
Sebastien Wong, Consillium Technology

- Publications Chair
Kok-Leong Ong, La Trobe University

- Organising Chairs
Wolfgang Mayer, University of South Australia
Cristina Garcia, University of South Australia

- Publicity Chair
Yee Ling Boo, RMIT

- Sponsorship Chair
Michael Bewong, University of South Australia

- Web Master
Vu Viet Hoang Pham, University of South Australia


**Steering Committee
Simeon Simoff (Chair), University of Western Sydney
Graham William (Chair), Microsoft
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’19 website: https://ausdm19.ausdm.org/
Contact the organisers of AusDM 2019 at ausdm19@ausdm.org
AusDM LinkedIn Group: https://www.linkedin.com/groups/4907891/