Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 10
2952-2954,2970

Fuzzy information extraction based on improved chaotic partition algorithm

Wan Fucheng1,2
1. Key Laboratory of National Language Intelligent Processing, Lanzhou 730030, China
2. Northwest Minzu University, Lanzhou 730030, China
DOI: 10.19734/j.issn.1001-3695.2018.03.0209

Abstract

In the environment of big data, the interference between the small disturbances of the data affects the fuzzy information extraction, which leads to the poor clustering characteristics of information extraction. This paper proposed a fuzzy information extraction method based on the improved chaotic partition algorithm. It reorganized the high dimensional data information flow with distributed structure, and used the Lorenz chaotic attractor as the training test set for the adaptive learning training of big data fuzzy information extraction. It used the phase space reconstruction technique match big data's chaotic attractor load with autocorrelation feature matching, and extracted the average mutual information feature quantity of fuzzy information. Through realizing the optimal clustering of fuzzy information, it realized the accurate extraction of fuzzy information according to the result of data clustering, carried out the feature compression of the extracted high-dimensional fuzzy information, and reduced the computational overhead. The simulation results show that, using this method to extract fuzzy information from big data sample sequence has good clustering property, strong ability to resist inter-class disturbance, and high accurate probability of fuzzy information extraction. It has a good application value in data mining and feature extraction.

Foundation Support

国家自然科学基金资助项目(61762076)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.03.0209
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 10
Section: Algorithm Research & Explore
Pages: 2952-2954,2970
Serial Number: 1001-3695(2019)10-015-2952-03

Publish History

[2019-10-05] Printed Article

Cite This Article

万福成. 基于改进混沌分区算法的模糊信息抽取 [J]. 计算机应用研究, 2019, 36 (10): 2952-2954,2970. (Wan Fucheng. Fuzzy information extraction based on improved chaotic partition algorithm [J]. Application Research of Computers, 2019, 36 (10): 2952-2954,2970. )

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  • Application Research of Computers Monthly Journal
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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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