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DPM 2020 : Discriminative Pattern Mining Workshop

Atlanta, Georgia, USA
Event Date: Dec 10, 2020 - Dec 13, 2020
Submission Deadline: Oct 01, 2020
Notification of Acceptance: Nov 01, 2020
Camera Ready Version Due : Nov 25, 2020


Association (frequent pattern) mining is a fruitful and important area of study that seeks (a) to discover what items (objects) appear frequently together and (b) to predict, given a set of objects, what other objects are likely to occur. Association mining has been successfully utilized for web log analysis, analysis of customer buying, biomedical knowledge mining, among others. However, a key drawback in association mining is the users need to take additional steps to make the information actionable. This includes, in many cases, in detecting what differences resides between groups, such that any changes are actionable. Research in this area finds a home in a number of related aread, including discriminative pattern mining, contrast mining, emerging pattern mining, action rule mining and subgroup discovery. The motivation in organizing this workshop the 2020 IEEE International Conference on Big Data is to attract novel papers in the development and application of algorithms within the above fields and to encourage conversations and idea exchange between the subfields.

Call For Paper

Topics of interest to this workshop include (but are not limited to):

  • Discriminative mining and learning in big data
  • Theory, applications, and core methods
  • Discriminative mining in large datasets
  • Predictive modeling/learning, clustering and data analysis that incorporates Discriminative mining
  • Incremental and/or streaming discriminative mining
  • Privacy/security in discriminative mining
  • Visualization techniques for utility discriminative mining
  • Applications of discriminative mining in healthcare, manufacturing, predictive and prescriptive maintenance, social media, etc.

Authors of accepted papers will be expected to present their research at the workshop.

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