Title: Research on the generation of correlation relations of electricity transmission based on improved Jaro-Winkler algorithm

Authors: Xiangrui Zong; Bing Feng; Ning Liu; Yuefan Du; Jian Zheng; Bin Zhou

Addresses: State Grid Tianjin Electric Power Company, Tianjin, 300300, China ' State Grid Tianjin Electric Power Company, Tianjin, 300300, China ' State Grid Tianjin Electric Power Company, Tianjin, 300300, China ' State Grid Tianjin Electric Power Company, Tianjin, 300300, China ' State Grid Tianjin Electric Power Company, Tianjin, 300300, China ' State Grid Tianjin Electric Power Company, Tianjin, 300300, China

Abstract: At present, the data correlation query method in the field of electric power marketing has problems such as low efficiency and low accuracy. This paper improves the Jaro-Winkler character similarity algorithm by combining the editing distance algorithm to improve the matching rate of field names in the data table. Experimental results based on 2,356 data tables show that the improved algorithm is applied to the data table association relationship query, and its accuracy reaches 98%. Based on the improved Jaro-Winkler algorithm and Echarts framework, a visual display system of association relationship of power marketing data table is developed, which provides auxiliary support for business personnel to use data independently and efficiently.

Keywords: Jaro-Winkler; string similarity; electricity marketing database; associative relationships.

DOI: 10.1504/IJCSYSE.2026.151354

International Journal of Computational Systems Engineering, 2026 Vol.10 No.1/2/3/4, pp.104 - 112

Received: 22 Sep 2023
Accepted: 04 Nov 2023
Published online: 26 Jan 2026 *

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