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PICKT: A Solution for Big Data Analysis

  • Tianrui Li
  • Chuan Luo
  • Hongmei Chen
  • Junbo Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9436)

Abstract

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.

Keywords

Big data Rough set Granular computing Incremental learning 

Notes

Acknowledgments

This work is supported by the National Science Foundation of China (Nos. 61175047 and 71201133) and NSAF (No. U1230117).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Tianrui Li
    • 1
  • Chuan Luo
    • 1
  • Hongmei Chen
    • 1
  • Junbo Zhang
    • 1
  1. 1.School of Information Science and TechnologySouthwest Jiaotong UniversityChengduChina

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