To register for this conference please register at the CEC 2003 conference web site. Registration for the conference is $150.

The conference will run from 9am to 5pm at the conference hotel (Rydges Lakeside). Lunch and morning/afternoon tea is provided for conference registrants.

The Australasian Data Mining Conference is devoted to the art and science of data mining: the analysis of (usually large) data sets to discover relationships and present the data in novel ways that are compact, comprehendible and useful for researchers and practitioners. We are paritcularly seeking from the Data Mining community updates of research and progress in the local context, new breakthroughs in data mining applications and algorithms, evolutionary approaches to Data Mining, and Bioinformatics and Data Mining.

The Conference Program is now available.

Data mining projects involve both the utilisation of established algorithms from machine learning, statistics, and database systems, and the development of new methods and algorithms, targeted at large data mining problems. Nowadays data mining efforts have gone beyond crunching databases of credit card usage or stored transaction records. They have been focusing on data collected in the health care system, art, design, medicine and biology and other areas of human endeavour.

This conference aims to bring together researchers and industry practitioners from different data mining groups in Australia and the region and to provide a forum for presenting and discussing their latest research and development in the area. The conference will facilitate the cross-disciplinary exchange of ideas.

Publication

As with the previous conference (AusDM02) all papers will be reviewed by a panel of international experts and will be published for the conference. Revised papers will be published by Springer-Verlag as a collected volume in the Lecture Notes in Computer Science series.

Topics of interest

The major topics of the conference include but are not limited to

• Data mining methods and algorithms
• Data cleaning and data linking
• High performance computing and data mining
• Infrastructure for data mining
• Health Data Mining
• Financial data mining
• Spatial and temporal data mining
• Multimedia and web data mining
• Data mining in design
• Data mining in e-Business environments and virtual communities
• Applications - lessons and experiences

We encourage submissions of `greenhouse' work, which present early stages of a cutting-edge research and development. Software demonstrations are also welcome. The format of the conference will accommodate full paper presentations and short presentations about a work in progress, overview of a data mining group or software demonstration.

Organisers

Simeon J Simoff	University of Technology, Sydney
Graham J Williams	Togaware Canberra
Markus Hegland	Australian National University

Program Committee

Mihael Ankerst	Boeing Corp
Michael Bohlen
Doug Campbell	SAS Australian and New Zealand
Jie Chen	CSIRO, Canberra
Peter Christen	Australian National University
Vladimir Estivill-Castro	Giffith University
Warwick Graco	Australian Taxation Office
Weiqiang Lin	Australian Taxation Office
Warren Jin	CSIRO, Canberra
Paul Kennedy	University of Technology, Sydney
Inna Kolyshkina	Pricewaterhouse Coopers
Tom Osborn	NUIX Pty Ltd
Francois Poilet	Parc Universitaire de Laval-Change
Chris Rainsford	DSTO Canberra
David Skillicorn	University of Queens
Marcel van Rooyen	Hutchison Communications
John Yearwood	University of Ballarat
Osmar Zaiane	University of Alberta

Further information from simeon@it.uts.edu.au or Graham.Williams@togaware.com.