Intelligent book recommendation system for libraries supported by gray wolf optimization algorithm DOI

J.X. Wang,

Yuhua Liang,

Jialin Zhao

et al.

Journal of Computational Methods in Sciences and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: May 12, 2025

This paper presents a library book recommendation system designed to improve effectiveness, utilizing the GWO algorithm. The architecture consists of three distinct layers: foundational data layer, processing and intelligent service. improved CGWO-KM algorithm is used cluster project attributes, search update mechanism gray wolf population applied find better initial clustering centers. Missing rating then filled in, user similarity calculated. A harmonized weighting factor eliminate correlation between ratings from different users. weighted comprehensively considers both influence neighboring Pearson coefficient combines factors with obtain final score, completing process for library’s books. results show that at 5th month time snapshot, predicted (6) historical borrowing dataset closely matches actual value (3.7). method proposed in this demonstrates an IGD mean close true optimal solution across various datasets literature, science popularization, history, art, novels, values 0.0012, 0.0023, 0.0014, 0.0021, 0.0020, respectively. non-dominated solutions three-dimensional space resource utilization, diversity, engagement are ideal 1. Moreover, has short time, accuracy ranges 0.882 0.993, providing personalized, high-quality services readers.

Language: Английский

Intelligent book recommendation system for libraries supported by gray wolf optimization algorithm DOI

J.X. Wang,

Yuhua Liang,

Jialin Zhao

et al.

Journal of Computational Methods in Sciences and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: May 12, 2025

This paper presents a library book recommendation system designed to improve effectiveness, utilizing the GWO algorithm. The architecture consists of three distinct layers: foundational data layer, processing and intelligent service. improved CGWO-KM algorithm is used cluster project attributes, search update mechanism gray wolf population applied find better initial clustering centers. Missing rating then filled in, user similarity calculated. A harmonized weighting factor eliminate correlation between ratings from different users. weighted comprehensively considers both influence neighboring Pearson coefficient combines factors with obtain final score, completing process for library’s books. results show that at 5th month time snapshot, predicted (6) historical borrowing dataset closely matches actual value (3.7). method proposed in this demonstrates an IGD mean close true optimal solution across various datasets literature, science popularization, history, art, novels, values 0.0012, 0.0023, 0.0014, 0.0021, 0.0020, respectively. non-dominated solutions three-dimensional space resource utilization, diversity, engagement are ideal 1. Moreover, has short time, accuracy ranges 0.882 0.993, providing personalized, high-quality services readers.

Language: Английский

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