Title: Comprehensive management method of financial data based on knowledge graph

Authors: Yang Yang

Addresses: College of Economics and Trade, Henan Polytechnic Institute, Nanyang, Henan, 473000, China

Abstract: To avoid financial data loss and enhance the read and write speed of financial data, a comprehensive financial data management method based on the knowledge graph is proposed. Firstly, complex features are automatically extracted from time-series data using CNN. Secondly, a distributed data storage architecture model is constructed, combined with a joint statistical strategy of multiple nonlinear components, to reconstruct the high-dimensional feature domain of financial time-series data and complete association rule mining. Finally, based on the mining results, a knowledge graph system is constructed, and intelligent protocols are deployed to ensure security and achieve comprehensive management of financial data. The experimental results indicate that the maximum amount of financial data loss achieved by this method is only 0.15 GB, while the read and write speed of financial data updates remains stable at 10 GB/s or above, which is 3 GB/s higher than that of existing methods.

Keywords: knowledge graph; financial data; integrated management; high-dimensional feature domain.

DOI: 10.1504/IJCAT.2026.154051

International Journal of Computer Applications in Technology, 2026 Vol.78 No.4, pp.314 - 322

Received: 11 Feb 2025
Accepted: 10 Jun 2025
Published online: 10 Jun 2026 *

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