Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Peter Christen, Paul J Kennedy, Jiuyong Li, Inna Kolyshkina, Graham J. Williams
Abstract
Peter Christen, Paul J Kennedy, Jiuyong Li, Inna Kolyshkina, Graham J. Williams
Abstract
The Australasian Data Mining Conference series AusDM, started in 2002, is the annual flagship meeting for data mining and analytics professionals in Australia. Both scholars and practitioners present the stateof- the-art in the field. Endorsed by the peak professional body, the Institute of Analytics Professionals of Australia, AusDM has developed a unique profile in nurturing this joint community. The conference series has grown in size each year from early workshops held in Canberra (2002, 2003) and Cairns (2004) to conferences in Sydney (2005, 2006). This year we are delighted to be co-hosted with the Twentieth Australian Joint Conference on Artificial Intelligence on the Gold Coast, Queensland, and the Second International Workshop on Integrating AI and Data Mining. This year's event has been supported by • Togaware, again hosting the website and the conference management system, coordinating the review process and other essential expertise; • Griffith University for providing the venue, registration facilities and various other support; • the Institute of Analytic Professionals of Australia (IAPA) for facilitating the contacts with the industry; • the ARC Research Network on Data Mining and Knowledge Discovery, for providing financial support; • the e-Markets Research Group, for providing essential expertise for the event; • the Australian Computer Society, for publishing the conference proceedings; • StatSoft for their support; • data mining postgraduate students from Queensland University of Technology for their local support. This year the Steering Committee and IAPA have recognised the importance of education in data mining and we have included a special panel session devoted to Data Mining Education. Also this year, for the first time, we have presented a Best Paper Award (voted by the peer review) and a Best Presentation Award (voted by conference delegates). We are delighted to expand the social program this year and hope that conference attendees will enjoy this extra time to make new contacts and to trade war stories. The conference program committee reviewed 69 submissions. This was an almost 20% increase in the number of submissions from last year. From these submissions 26 were selected for publication and presentation. This was an acceptance rate of 38%. AusDM follows a rigid double blind peer-review process and ranking-based paper selection process. All papers were extensively reviewed by at least three referees drawn from the program committee. We would like to note that the cut-off threshold has been high (5 on a 7 point scale). This is testament to the high quality of submissions. We would like to thank all those who submitted their work to the conference. We will continue to extend the conference format to be able to accommodate more presentations. We are proud to include in these proceedings the papers from the Second International Workshop on Integrating AI and Data Mining. Papers published in both volumes by the Australian Computer Society are indexed and available for download. Data mining and analytics today have advanced rapidly from the early days of pattern finding in commercial databases. They are now a core part of business intelligence and inform decision making in many areas of human endeavour including science, business, health care and security. Mining of unstructured text, semi-structured web information and multimedia data have continued to receive attention, as have professional challenges to using data mining in industry. Accepted submissions have been grouped into seven sessions reflecting these application areas. Three invited industry keynote sessions put the research into context.
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The Australasian Data Mining Conference series AusDM, started in 2002, is the annual flagship meeting for data mining and analytics professionals in Australia. Both scholars and practitioners present the stateof- the-art in the field. Endorsed by the peak professional body, the Institute of Analytics Professionals of Australia, AusDM has developed a unique profile in nurturing this joint community. The conference series has grown in size each year from early workshops held in Canberra (2002, 2003) and Cairns (2004) to conferences in Sydney (2005, 2006). This year we are delighted to be co-hosted with the Twentieth Australian Joint Conference on Artificial Intelligence on the Gold Coast, Queensland, and the Second International Workshop on Integrating AI and Data Mining. This year's event has been supported by • Togaware, again hosting the website and the conference management system, coordinating the review process and other essential expertise; • Griffith University for providing the venue, registration facilities and various other support; • the Institute of Analytic Professionals of Australia (IAPA) for facilitating the contacts with the industry; • the ARC Research Network on Data Mining and Knowledge Discovery, for providing financial support; • the e-Markets Research Group, for providing essential expertise for the event; • the Australian Computer Society, for publishing the conference proceedings; • StatSoft for their support; • data mining postgraduate students from Queensland University of Technology for their local support. This year the Steering Committee and IAPA have recognised the importance of education in data mining and we have included a special panel session devoted to Data Mining Education. Also this year, for the first time, we have presented a Best Paper Award (voted by the peer review) and a Best Presentation Award (voted by conference delegates). We are delighted to expand the social program this year and hope that conference attendees will enjoy this extra time to make new contacts and to trade war stories. The conference program committee reviewed 69 submissions. This was an almost 20% increase in the number of submissions from last year. From these submissions 26 were selected for publication and presentation. This was an acceptance rate of 38%. AusDM follows a rigid double blind peer-review process and ranking-based paper selection process. All papers were extensively reviewed by at least three referees drawn from the program committee. We would like to note that the cut-off threshold has been high (5 on a 7 point scale). This is testament to the high quality of submissions. We would like to thank all those who submitted their work to the conference. We will continue to extend the conference format to be able to accommodate more presentations. We are proud to include in these proceedings the papers from the Second International Workshop on Integrating AI and Data Mining. Papers published in both volumes by the Australian Computer Society are indexed and available for download. Data mining and analytics today have advanced rapidly from the early days of pattern finding in commercial databases. They are now a core part of business intelligence and inform decision making in many areas of human endeavour including science, business, health care and security. Mining of unstructured text, semi-structured web information and multimedia data have continued to receive attention, as have professional challenges to using data mining in industry. Accepted submissions have been grouped into seven sessions reflecting these application areas. Three invited industry keynote sessions put the research into context.
Key concepts: Analytics, Publishing, Session (web analytics), Library science, Engineering, Public relations, Data science, Political science