Title: An optimisation method for intelligent legal information query based on association rule data mining algorithm

Authors: Haimei Yu

Addresses: Law School, Weifang University, Weifang, Shandong, China

Abstract: Aiming to address the issues of low accuracy, low recall and long average response time in current intelligent legal information query optimisation methods, a new optimisation method for intelligent legal information query based on association rule data mining algorithm is proposed. The association rule data mining algorithm based on ant colony algorithm is optimised, legal information using the optimised association rule data mining algorithm is obtain, and missing legal information is synchronised and filled. An intelligent legal information query optimisation model based on the processed legal information is built, and an improved genetic algorithm to solve the model is used, thereby achieving intelligent legal information query optimisation. The experimental results show that the maximum accuracy of the proposed method for intelligent legal information query is 98.86%, the maximum recall rate is 97.21% and the average response time varies between 0.21 s and 0.65 s, demonstrating high precision and efficiency.

Keywords: association rule data mining algorithm; legal information; optimisation method for intelligent legal; ant colony algorithm; improved genetic algorithm.

DOI: 10.1504/IJIPT.2025.148573

International Journal of Internet Protocol Technology, 2025 Vol.18 No.3, pp.163 - 173

Received: 24 Feb 2025
Accepted: 26 Apr 2025
Published online: 12 Sep 2025 *

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