The 1st ICDM Workshop on Dynamic Feature Mining (DFM’19)
Inconjunction with the IEEE International Conference on Data Mining (IEEE ICDM 2019), Beijing, China, November 8-11, 2019

Description of the workshop

The emerging of various data collecting ways lead to increasing data sets with dynamic features in all areas of science, engineering and businesses. These include sensor data in monitoring systems, trading data in E-business systems and voting data in recommendation systems among many others. For a number of reasons, classical data analysis methods inadequate, questionable, or inefficient when faced with dynamic feature data analyses:

  • The evolving of dynamic feature violates the traditional independent and identically distributed assumption in the areas of data mining and machine learning.

  • The evolving of features may lead to storage problem if the algorithms are batch-model and all the data are utilized during training.

  • The accumulation of features will lead to high dimensional data, which will cause curse of dimensionality reduction problem.

  • The accumulation of features will also lead to computational issues, especially when the frequency of feature changes is high.

Topics

This workshop aims to promote new advances and research directions to address the challenging problems arisen from the evolving nature of features in data mining. Topics of interest include all aspects of dynamic feature mining, including but notlimited to:

  • Systematic researches of how the evolving nature of features affects data mining methods.

  • New mining algorithms for dynamic features in supervised, semi-supervised or unsupervised way.

  • Dimensionality reduction approaches for accumulated of various types of dynamic features.

  • Storage or computation scalable approaches for evolving features.

  • Theoretical underpinning of mining historical features.

  • Datamining applications to real problems in science, engineering or businesses where the features are dynamic.

  • Other learning paradigms arisen from the dynamic nature of features.

Paper submission

High quality original submissions are welcomed for oral and poster presentation at the workshop. The page limit of workshop papers is 8 pages in the standard IEEE 2-column format(https://www.ieee.org/conferences/publishing/templates.html), including the bibliography and any possible appendices. Reviewing is blind. Therefore, please do not include author identifying information. All papers must be formatted according to the IEEE Computer Society proceedings manuscript style, following IEEE ICDM 2019 submission guidelines, which are the same as for the main conference (except the page limit). All accepted workshop papers will be published in the IEEE Computer Society DigitalLibrary (CSDL) and IEEE Xplore, and indexed by EI.

Important dates

  • Submission deadline: 7th August, 2019.

  • Workshop paper notifications: September 4, 2019

  • Camera-ready deadline for the final version of accepted papers: September 8, 2019

Registration& Expenses

Every workshop paper must haveat least one full paid conference registration in order to be published. Check the main conference pages for details.

Program Committee

TBA

Workshop organisation

Chenping Hou, hcpnudt@hotmail.com, National University of Defense Technology, China

Min-Ling Zhang, zhangml@seu.edu.cn, Southeast University, China

Cheng Deng, Chdeng.xd@gmail.com, Xidian University, China

Yuhua Qian, jinchengqyh@126.com, Shanxi University, China

Scholars

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