PICKT: A Solution for Big Data Analysis
Tianrui Li, Chuan Luo, Hongmei Chen, Junbo Zhang · Lecture notes in computer science · 2015
Emerging information technologies and application patterns in modern information society, e.g., Internet, Internet of Things, Cloud Computing and Tri-network Convergence, are growing in an amazing speed which causes the advent of the era of Big Data. Big Data is often described by using five V’s: Volume, Velocity, Variety, Value and Veracity. Exploring efficient and effective data mining and knowledge discovery methods to handle Big Data with rich information has become an important research topic in the area of information science. This paper focuses on the introduction of our solution, PICKT, on big data analysis based on the theories of granular computing and rough sets, where P refers to parallel/cloud computing for the Volume, I refers to incremental learning for the Velocity, C refers to composite rough set model for the Variety, K refers to knowledge discovery for the Value and T refers to three-way decisions for the Veracity of Big Data.