INTRODUCTION

In the big data era, with the enrichment of data collection and description measures, a wide array of data in various formats are collected much easier than before. It is significant to discover the knowledge hidden in the mass by comprehensive understanding and learning to realize the data intelligence, which can help human in various dimensions, such as intelligent decisions and predictive services. However, the volume, heterogeneous, low-quality and multimodal characteristics of the collected data pose great challenges to the design of knowledge discovery methods. Therefore, this workshop aims to provide a forum to present the state-of-the-art advancements on knowledge discovery for big data, which include related surveys, algorithms, platforms, systems and applications.

Call for Papers pdf

The topics include but not limited to:
  • Acquisition, transmission, storage, index and visualization for big data
  • Innovative methods for big data analytics
  • Multimodal data fusion
  • Cross-modal reasoning and retrieval
  • Domain adaption and transfer learning
  • Zero-shot and few-shot learning
  • Deep learning and reinforcement learning
  • Knowledge graphs
  • Natural language processing
  • Parallel, accelerated, and distributed algorithms and frameworks for big data
  • Security, privacy and trust in big data
  • Big data in Internet of Things
  • Methods for academic, traffic, medical, financial, and judicial big data
  • Other methods, models, architectures and applications related to big data

  • IMPORTANT DATES

  • Paper Submission Deadline: March 10, 2020
  • Acceptance Notification: April 1, 2020
  • Camera-ready Submission: May 10, 2020
  • Paper Submission

    Papers should be prepared in IEEE CS format within 6 pages. IEEE formatting information: ( link )

    Authors are invited to submit their original research work using IEEE CS Proceedings format via PICOM 2020 EDAS (https://edas.info/N26908). Ps: Log on the system and choose the Track of International Workshop on Knowledge Discovery for Big Data.

    All accepted papers will be published by IEEE (IEEE-DL and EI indexed) in Conference Proceedings.

    Committees

  • Organizing Chair
  • Fangming Zhong, Dalian University of Technology, China

  • Organizing Co-Chair
  • Qingchen Zhang, St. Francis Xavier University, Canada

    Liang Zhao, Dalian University of Technology, China

    Haozhe Wang, University of Exeter, UK

  • Program Committee Chair
  • Xiaochen Li, University of Luxembourg, Luxembourg

    Liang Zou, China University of Mining and Technology, China

    Yujia Zhu, University of Exeter, UK

    Aiping Liu, University of Science and Technology of China, China

  • International Committee Chair
  • Shi Chen, Emporia State University, USA

    Yi Yang, Beihang University, China

    Yonglin Leng, Bohai University, China

  • Advisory Chair
  • Zhikui Chen, Dalian University of Technology, China

    Calgary

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    Get In Touch

  • Dr. Fangming Zhong fmzhong@dlut.edu.cn
  • Dr. Liang Zhao liangzhao@dlut.edu.cn
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