Special Session on "When Evolutionary Computation Meets

Data Mining"


Many of the tasks carried out in data mining and machine learning, such as feature subset selection, associate rule mining, and model building, can be transformed as optimization problems. Thus it is very natural that Evolutionary Computation (EC), has been widely applied to these tasks in the fields of data mining (DM) and machine learning (ML), as an optimization technique.

On the other hand, EC is a class of population-based iterative algorithms, which generate abundant data about the search space, problem feature and population information during the optimization process. Therefore, the data mining and machine learning techniques can also be used to analyze these data for improving the performance of EC. A lot of successful applications have been reported, including the creation of new optimization paradigm such as Estimation of Distribution Algorithm, the adaptation of parameters or operators in an algorithm, mining the external archive for promising search regions, and so on.

However, there remain many open issues and opportunities that are continually emerging as intriguing challenges for bridging the gaps between EC and DM. The aim of this special session is to serve as a forum for scientists in this field to exchange the latest advantages in theories, technologies, and practice.

We invite researchers to submit their original and unpublished work related to, but not limited to, the following topics:

Paper Submission:

All papers should be submitted electronically through IEEE CEC 2017 website at http://www.cec2017.org/ To submit your papers to the special session, please select the Special Session in the Main Research topic. For more submission information please visit: http://www.cec2017.org/ All accepted papers will be published in the IEEE CEC 2017 electronic proceedings.


Zhun Fan
Shantou University, China
E-mail: zfan@stu.edu.cn

Xinye Cai
Nanjing University of Aeronautics and Astronautics, China
E-Mail: xinye@nuaa.edu.cn

Chuan-Kang Ting
National Chung Cheng University, Taiwan
E-Mail: ckting@cs.ccu.edu.tw

Program Committee (Provisional):