The Big Data Partitioning and Mining (BDPM) workshop is a half-day event and co-located with IEEE ICBK 2017. It aims to provide a unique opportunity for researchers and practitioners working on big data processing, data-intensive computing, and big data mining, to exchange innovative ideas and thoughts on knowledge discovery and pattern mining from big data, especially focusing on big data mining, data partitioning, fragmented knowledge management, and big knowledge synthesizing. The workshop invites original research papers belonging to, but not limited to, the following topics

Topics of Interest

Topics covering academic research and industrial applications into Big Knowledge will include, but not limited to:



Data preprocessing for web data, graph data, and big social data


Probabilistic partitioning techniques for structured/unstructuredsemi-structured big data


Graph partitioning theories and methods for big social network data


Pattern synthesizing for partitioned big data


Local pattern analysis for multi-source data


Online learning for big streaming data


Big knowledge management for advertising and business analysis


Knowledge discovery from segmented big data


Global knowledge approximation by analyzing local data


Applications and services of big knowledge in all domains including web, medicine, education, healthcare, and business


Important Dates

Paper submission deadline: 10 May, 2017


Notification of acceptance: 30 May, 2017


Camera-ready of accepted paper: 15 June, 2017


Workshop date: 9-10 August, 2017


Guide Lines for Submission

The submissions should follow IEEE Conference template, with double-column and not exceeded 6 pages. Accepted papers are included in the proceedings of the IEEE ICBK main conference, and will be indexed by EI. Selected best papers are recommended to SCI journal Multimedia Tools and Applications for publication. Please submit your manuscript to the workshop at https://wi-lab.com/cyberchair/2017/icbk17/index.php.