Feature mining method of information system operation and maintenance big data based on window function

Article type: Research Article

Authors: Sun, Ruohan^{; *} | Hu, Meihui | Cao, Jinping | Xiao, Wanxing | Guo, Xinying

Affiliations: Department of Information, State Grid Xin Jiang Electric Power Corporation Information & Telecommunication Company, Urumqi 830092, China

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: In this paper, a window function based feature mining method for the operation and maintenance of big data in information system is proposed. The time clustering feature vector is combined with window function to reduce the dimension of operation and maintenance data of high-dimensional information system. The operation and maintenance data feature subset is segmented according to the similar feature level, and the redundant features of operation and maintenance data are removed to complete the information system operation and maintenance big data feature mining. The simulation results show that the proposed method has better clustering effect, fewer iterations and shorter mining time.

Keywords: Window function, information system, operation and maintenance big data, feature mining

DOI: 10.3233/WEB-210462

Journal: Web Intelligence, vol. 19, no. 1-2, pp. 135-145, 2021