Scope of the workshop

Utility-driven mining and learning from data has received emerging attentions from KDD communities due to its high potential in wide applications, covering finance, biomedicine, manufacturing, e-commerce, social media, etc. Some current research topics in utility-driven mining focused are for example to discover patterns of high value (eg, high profit) in large databases, analyzing/learning the important factors (eg, economic factors) in the data mining or machine learning process, and learning models that optimize some given utility functions. One of the popular applications of utility mining and learning is the analysis of large transactional databases to discover high-utility itemsets, which consist of sets of items that generate a high profit when purchased together.

The workshop aims at bringing together academic and industrial researchers and practitioners from data mining, machine learning and other interdisciplinary communities, in the collaborative effort of identifying and discussing major technical challenges, recent results and potential topics on the emerging fields of Utility-Driven Mining and Learning. This workshop will focus on real world experiences, inherent challenges, as well as new research methods/applications.

Following the success of the UDML 2018 , UDML 2019, and UDML 2020, the fourth Utility-Driven Mining and Learning (UDML 2021) workshop will discuss a broad variety of topics related to utility-driven mining and learning, including:

  • Theory and core methods for utility mining and learning
  • Utility pattern mining in large datasets, e.g., high utility itemset mining, high utility sequential patterns/rules mining, high utility episode mining, and novel pattern types
  • Analysis and learning of novel utility factors in data mining and machine learning processes
  • Predictive modeling/learning, clustering and link analysis that incorporate utility factors
  • Game-theoretic multiagent system
  • Utility-based decision-making, planning and negotiation
  • Models for utility optimizations and maximization
  • Utility mining and learning in dynamic databases
  • Utility mining and learning in IoT environment
  • Utility mining and learning in streams
  • Utility mining and learning in big data
  • Knowledge representations for utility patterns
  • Knowledge integration and fusion of utility patterns
  • Privacy preserving and security issues in utility mining/learning
  • AI and ML models incorporated with utility-driven concept
  • Visualization techniques for utility mining/learning
  • Open-source software/libraries/platform
  • Innovative applications in interdisciplinary domains, like finance, biomedicine, healthcare, manufacturing, e-commerce, social media, education, etc.
  • New, open, or unsolved problems in utility-driven mining and learning

The UDML 2021 workshop will be held on December 7, 2021 virtually at part of the IEEE ICDM 2021 conference.

All accepted papers will be published in the IEEE ICDM 2021 Workshop proceedings (published by IEEE and EI-indexed)

Moreover, the top papers will be invited for submitting extended versions to a special journal issue in the Intelligent Data Analysis journal (SCI-indexed).

A best paper award will be awarded.

For any questions, please contact the organizing committee.

There is also a CFP in text format.

Important dates

  • Paper submission deadline: September 3, 2021
  • Paper notifications: September 27, 2021
  • Camera-ready deadline and copyright forms: October 1, 2021
  • Workshop date: December 7 2021

Proceedings

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