Personalized Retrieval Method of English Teaching Resources Based on Improved Lion Pride Algorithm

This look introduces a better technique for the personalized retrieval of English instructional resources, integrating Particle Swarm Optimization (PSO) with the lion pleasure set of rules (LPA). The considerable extent and diverse nature of educational assets pose sizeable challenges in effective retrieval, especially, in assembly-precise user wishes. Traditional LPA, while beneficial, falls brief in international seek performance and accuracy. This study aims to address these boundaries by embedding PSO into LPA, appreciably improving its worldwide seek functionality and convergence pace. The proposed hybrid algorithm demonstrates superior performance in experimental exams on useful resource databases in English coaching, showcasing marked enhancements in both accuracy and performance of useful resource retrieval. These improvements advise a significant leap forward in developing sophisticated, personalized resource retrieval system and may probably revolutionize the field of instructional technology. This paper’s work no longer only contributes to the optimization of educational aid retrieval; however, it may provide a possible framework for comparable demanding situations in different domain names.