Algorithm Research & Explore
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2643-2646,2685

Failures sequence pattern mining algorithm based on text analysis

Chang Wenbing
Yuan Xinglong
Zhou Shenghan
Li Lei
School of Reliability & System Engineering, Beihang University, Beijing 100191, China

Abstract

For textual data with poor structured degree and different expression forms, this paper proposed a failures sequence pattern mining algorithm based on text information to explore the time sequence relationship between failures. In order to mine the failures rules from the text, firstly, it quantified the text information, measure the similarity of the failures information, and classified the failures that express the same meaning into one class. On this basis, it proposed the concept of maximum window threshold and minimum concurrence threshold based on failures characteristics, and built a mining algorithm framework for failures sequence pattern. Finally, it extracted sequential failures patterns from a certain aircraft, and found out the correct failures sequence relationship. The example shows that the proposed algorithm is correct and effective.

Foundation Support

国家自然科学基金资助项目(71501007)
航空科学基金资助项目
北航研究生教育发展基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.02.0142
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 9
Section: Algorithm Research & Explore
Pages: 2643-2646,2685
Serial Number: 1001-3695(2019)09-018-2643-04

Publish History

[2019-09-05] Printed Article

Cite This Article

常文兵, 苑星龙, 周晟瀚, 等. 基于文本分析的故障序列模式挖掘算法 [J]. 计算机应用研究, 2019, 36 (9): 2643-2646,2685. (Chang Wenbing, Yuan Xinglong, Zhou Shenghan, et al. Failures sequence pattern mining algorithm based on text analysis [J]. Application Research of Computers, 2019, 36 (9): 2643-2646,2685. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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