【会议征文】The 4th Workshop on Complex Methods for Data and Web Mining(CMDWM)

  • 李秀明
  • 发布于 2017-03-13
  • 217

New real world applications of data mining and machine learning have shown that popular methods may appear to be too simple and restrictive. Mining more complex, larger and generally speaking “more difficult” data sets pose new challenges for researchers and ask for novel and more complex approaches. We organize this workshop where we want to promote research and discussion on more complex and advanced methods for the particularly demanding data and web mining problems. Although we welcome submissions concerning methods based on different principles, we would like also to see among them new research on using optimization techniques. The new data and web mining problems are definitely more complex than traditional ones and they could result in more difficult non-convex optimization formulations. We would like to focus interest of data mining community on various challenging issues which come up while using complex methods to deal with the difficult data mining problems.

Suggested topics include (but are not limited to) the following:

  • Optimization methods for data or web mining and machine learning
  • Multiple criteria perspectives in data mining and learning
  • Supporting human evaluation of patterns discovered from data
  • Combined classifiers for complex learning problems
  • New methods for constructing and evaluating on-line recommendation
  • Mining “difficult” data – concerning different aspects of data difficulty (time changing, class imbalanced, partially labeled, multimedia, semi-structured or graph data)
  • Mining spatial data and images
  • Identifying the most challenging applications and key industry drivers (where both theories and applications point of views have to meet together)

Submission Guidelines:

CMDWM invites original high-quality papers. Each accepted paper will be allocated 4 pages in the proceedings and all papers accepted for workshops will be included in the Workshop Proceedings published by the IEEE Computer Society Press, and will be available at the workshops.

May 22, 2017: Submission of Workshop papers

June 19, 2017: Notification of Workshop paper acceptance

July 17, 2017: Camera-Ready Papers (Workshops)

Workshop Oganizers

Chinese Academy of Sciences Research Center on Fictitious Economy & Data Science

Key Laboratory of Big Data Mining and Knowledge Management and also with Research Center on Fictitious Economy & Data Science

Workshop organizers:

Yong Shi

Chinese Academy of Sciences Research Center on Fictitious Economy & Data Science

E-mail: yshi@ucas.ac.cn

Lingfeng Niu

Chinese Academy of Sciences Research Center on Fictitious Economy & Data Science

E-mail: niulf@ucas.ac.cn

The postal mailing address: Room 215, Buliding 6, No 80, Zhongguancun Donglu,

Haidian District, Beijing, 100190

Name of the corresponding workshop organizer: Lingfeng Niu

Program Committee

Xiaojun Chen

The Hong Kong Polytechnic University, HK, China

Zhengxin Chen

University of Nebraska at Omaha, USA

Kun Guo

University of the Chinese Academy of Sciences, China

Jing He

Victoria University, Australia

Gang Kou

University of Electronic Science and Technology of China, China

Kin Keung Lai

City University of Hong Kong, Hong Kong, China

Heeseok Lee

Korea Advanced Institute Science and Technology, Korea

Jiming Peng

University of Illinois at Urbana-Champaign, USA

Yi Peng

University of Electronic Science and Technology of China, China

Zhiquan Qi

University of the Chinese Academy of Sciences, China

Yingjie Tian

Chinese Academy of Sciences Research Center on Fictitious Economy & Data Science, China

Bo Wang

University of Internal Business and Economics, China

Jianping Li

Chinese Academy of Sciences, China

Lingling Zhang

University of Chinese Academy of Sciences, China

Yanchun Zhang

Victoria University, Australia

Ning Zhong

Maebashi Institute of Technology, Japan

Xiaofei Zhou

Chinese Academy of Sciences, China