Earticle

초록

영어

Using data mining technology to analyze the huge amounts of meteorological data plays an important role in improving the accuracy of weather forecasts. After analyzed the features of meteorological data, a distributed meteorological data mining models using the pattern structure in formal concept analysis is proposed in this paper. Since there exists large numerical, boolean, and geographic concepts in meteorological data, using classic methods of formal concept analysis needs to build single-valued formal context. This paper adopts concept lattice pattern structure to avoid such conversions and the results of rules mining have higher readability and efficiency. This pattern structure of concept lattice is extended to the distributed model to improve data processing capability.

목차

Abstract
 1. Introduction
 2. Basic Definition of Pattern Structure
 3. Similar Computing in Meteorological Data
  3.1. Numerical Interval
  3.2. Geographical Regional Information
  3.3. Boolean Value
  3.4 Mixed Type Vector
 4. The Construction of the Pattern of Concept Lattice
  4.1 The Conversions of Pattern Structure
  4.2 The Construction of the Pattern of Concept Lattice
 5. Experimental Results and Analysis
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Xiajiong Shen [ Institute of Data and Knowledge Engineering, Henan University, Kaifeng, Henan 475004, China ]
• Lei Zhang [ Institute of Data and Knowledge Engineering, Henan University, Kaifeng, Henan 475004, China ]
• Daojun Han [ Institute of Data and Knowledge Engineering, Henan University, Kaifeng, Henan 475004, China ]
• Peiyan Jia [ Institute of Data and Knowledge Engineering, Henan University, Kaifeng, Henan 475004, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605