Kaohsiung, Taiwan, November 18-21, 2019
Scope
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.
Proposed submissions should be original, unpublished, and novel for in-depth research. Topics include but not limited to:
· Acquisition, transmission, storage, index and visualization for big data
· Innovative methods for big data analytics
· Multimodal data fusion
· Domain adaption and transfer 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
Paper Submission Guideline
Papers should be prepared in IEEE CS format and submitted via the KDBD 2019 web site, under construction. Papers should be within 6 pages.
IEEE formatting information: http://www.ieee.org/conferences_events/conferences/publishing/templates.html.
Important Date
Paper submission deadline: June 10, 2019
Acceptance Notification: June 20, 2019
Workshop Committee Members
Organizing Chair:
Liang Zhao, Dalian University of Technology, China
Co-Chair:
Qingchen Zhang, St. Francis Xavier University, Canada
Fangming Zhong, Dalian University of Technology, China
Haozhe Wang, University of Exeter, UK
Program Committee Chair:
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
Meng Lei, China University of Mining and Technology, China