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活动简介

The Australasian Data Mining Conference (AusDM) 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.

征稿信息

重要日期

2018-08-03
初稿截稿日期

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

  • Academic submissions: Regular academic submissions can be made in Research Track reporting on research progress, with a paper length up to 12 pages. For academic submissions we will use a double-blind review process, i.e. paper submissions must NOT include author names or affiliations (and also not acknowledgements referring to funding bodies). Self-citing references should also be removed from the submitted papers (they can be added on after the review) for the double blind reviewing purpose.
  • Industry submissions: Submissions can be made in the Application Track to report on specific data mining implementations and experiences in governments and industry projects. Submissions in this category can be up to 12 pages. The review process for these submissions will also be double-blind. A special committee made of industry representatives will assess industry submissions. 
  • Industry Showcase submissions: Submission from industry and government 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 one page Abstract only. The review process for these submissions will also be double-blind.

征稿范围

Topics of interest include, but are not restricted to:

  • Applications of Data Mininig and Case Studies
  • Big Data Analytics
  • Biomedical and Health Data Mining
  • Business Analytics
  • Computational Aspects of Data Mining
  • Data Integration, Matching and Linkage
  • Data Mining Education
  • Data Mining in Security and Surveillance
  • Data Preparation, Cleaning and Preprocessing
  • Data Stream Mining
  • Implementations of Data Mining in Industry
  • Integrating Domain Knowledge
  • Knowledge Discovery and Presentation
  • Link, Tree, Graph, Network and Process Mining
  • Multimedia Data Mining
  • Mobile Data Mining
  • New Data Mining Algorithms
  • Privacy-preserving Data Mining
  • Spatial and Temporal Data Mining
  • Text Mining
  • Web and Social Network Mining
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重要日期
  • 会议日期

    11月28日

    2018

    11月30日

    2018

  • 08月03日 2018

    初稿截稿日期

  • 11月30日 2018

    注册截止日期

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