Discriminative Pattern Mining Workshop

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 areas, 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.

For the ease of use, when using Discriminative Mining, we use the term to include (but not limited to), discriminative pattern mining, contrast mining, emerging pattern mining, action rule mining and subgroup discovery.

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.

Paper Format and Submission

  • Please submit a full-length paper (up to 10 page IEEE 2-column format) through the online submission system.
  • Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see Formatting Instructions below).

Formatting Instructions

Important Dates

  • Paper Deadline: October 1, 2020 October 24, 2020
  • Author notification: November 1, 2020
  • Camera-Ready Submission: November 25, 2020
  • Workshop Day: December 10-13, 2020 Exact Day To Be Determined

Workshop Chairs

  • Ryan Benton, School of Computing, University of South Alabama
  • Tom Johnsten, School of Computing, University of South Alabama
  • Suresh Choubey, School of Computing, University of South Alabama

Presented Papers

  • Jennifer Brooks and Abdou Youssef, "Discriminative Pattern Mining for Natural Language Metaphor Generation"
  • Wyatt Green, Tom Johnsten, and Ryan Benton, "TADS: Transformation of Anomalies in Data Streams"

Program Committee

  • Elshaimma Ali, Sysco
  • Jian Chen, University of North Alabama
  • Djellel Difallah, Wikimedia Foundation
  • Jennifer Lavergne, McNeese State University
  • Patrick Luckett, Washington University School of Medicine in St. Louis
  • Satya Katragadda, University of Louisiana at Lafayette
  • Murali Pusala, AT&T
  • Vijay V. Raghavan, University of Louisiana at Lafayette