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    1. 【call for paper】The 7th Workshop on Complex Methods for Data and Web Mining(CMDWM)

      • 發布于 2020-05-13
      • 23352

      The 7th Workshop on Complex Methods for Data and Web Mining

      The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT '20)

      14-17 December 2020, Melbourne, Australia

      Call For Paper

      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.

      Submission deadline: 1st July, 2020

      Acceptance deadline: 20th September, 2020

      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

      Yang Xiao

      University of Chinese Academy of Sciences, China

      Pei Quan

      University of Chinese Academy of Sciences, China

      Yi Qu

      University of Chinese Academy of Sciences, China

      Minglong Lei

      Beijing University of Technology, Beijing, China.

       

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