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.
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