Flexible Frameworks for Actionable Knowledge Discovery

@article{Cao2010FlexibleFF,
  title={Flexible Frameworks for Actionable Knowledge Discovery},
  author={Longbing Cao and Yanchang Zhao and Huaifeng Zhang and Dan Luo and Chengqi Zhang and E. K. Park},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2010},
  volume={22},
  pages={1299-1312}
}
Most data mining algorithms and tools stop at the mining and delivery of patterns satisfying expected technical interestingness. There are often many patterns mined but business people either are not interested in them or do not know what follow-up actions to take to support their business decisions. This issue has seriously affected the widespread employment of advanced data mining techniques in greatly promoting enterprise operational quality and productivity. In this paper, we present a… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 51 CITATIONS

An Efficient Parallel High Utility Sequential Pattern Mining Algorithm

Chunkai Zhang, Yiwen Zu
  • 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
  • 2019
VIEW 12 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

A high coherent utility fuzzy itemsets mining algorithm

  • 2012 International Conference on Information Security and Intelligent Control
  • 2012
VIEW 7 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Social Security and Social Welfare Data Mining: An Overview

  • IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
  • 2012
VIEW 6 EXCERPTS
CITES BACKGROUND & METHODS

Action extraction from social networks

  • Journal of Intelligent Information Systems
  • 2019
VIEW 1 EXCERPT

Negative Sequence Analysis: A Review

  • ACM Comput. Surv.
  • 2019
VIEW 1 EXCERPT
CITES BACKGROUND

Data Semantics Meets Knowledge Discovery in Databases

  • A Comprehensive Guide Through the Italian Database Research
  • 2018
VIEW 1 EXCERPT
CITES BACKGROUND

Interactive Probabilistic Post-Mining of User-Preferred Spatial Co-Location Patterns

  • 2018 IEEE 34th International Conference on Data Engineering (ICDE)
  • 2018
VIEW 1 EXCERPT
CITES BACKGROUND

FILTER CITATIONS BY YEAR

2010
2019

CITATION STATISTICS

  • 4 Highly Influenced Citations

References

Publications referenced by this paper.
SHOWING 1-10 OF 38 REFERENCES

Combined Mining: Discovering More Informative Knowledge in e-Government Services

L. Cao, H. Zhang, Y. Zhao, C. Zhang
  • technical report, Univ. of Technology Sydney, 2008.
  • 2008
VIEW 8 EXCERPTS
HIGHLY INFLUENTIAL

Action Rules Mining.

Zbigniew W. Ras, Elzbieta M. Wyrzykowska, Li-Shiang Tsay
  • 2009
VIEW 1 EXCERPT

Metasynthesis: M-Space, M-Interaction, and M-Computing for Open Complex Giant Systems

  • IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
  • 2009
VIEW 1 EXCERPT