There are several important aspects to mining patterns from big data. (1) data collection: how to collect meaningful and high-quality data effectively, without compromising personal privacy in different research domains; (2) pattern mining: how to design appropriate algorithms for dealing with large data sets that are beyond the ability of commonly used software tools to capture, curate, manage, and process within a tolerable elapsed time; (3) pattern visualization: how to present mining results in a more intuitive way, and how to abstract key information to visualize the relationship between data; and (4) practical application: how pattern mining algorithms apply to the real-world.

The topics of interest related to this workshop include, but are not limited to:

Data collection
Data cleaning
Data visualization
Pattern mining technique:
Association rule mining
Sequential pattern mining
Graph analysis
Time series analysis
Application:
Social network
Recommendation
Mobile
Sensor network
Bioinformatics
E-commerce
Health care