Personalized Literature Recommendation Algorithm Based on Log Mining

doi:10.3969/j.issn.1006-2475.2025.12.005

Abstract

Abstract: Abstract: In recent years, the exploration of personalized recommendation technology has increasingly occupied the core position in the field of recommendation system research. Among them, literature recommendation, as an important branch of this field, is receiving more and more attention and in-depth research. For the problems of that the current scientific and the literature recommendation algorithm in technological literature discovery system do not take into account the user’s behavior preferences and a large number of users cannot be recommended with literature due to sparse user data, this study proposes a personalized literature recommendation algorithm based on log mining. First of all, this study initializes the user behavior record log into a user-literature scoring matrix, and then in the process of in-depth analysis of user interest preferences, comprehensively considers the characteristics of global projects and local scoring information, and designs a user interest preference algorithm with the principle of Haiming’s closeness. Finally, the algorithm is fused with the weighted JMSD similarity algorithm to expand the coverage of the recommendation algorithm, and then greatly improve the accuracy of the recommendation results. The actual user behavior log data of NSTL literature service system was used in the experiment. The experimental results show that the algorithm’s overall performance is better than other baseline algorithms, with an average improvement of 0.8%, 3.2% and 1.9% in Precision, Recall and F1, which verified the effectiveness of the proposed algorithm. The research results can be applied to the literature discovery platform to further strengthen the intelligent level of document information resource service.

Key words: Key words: log mining, user preferences, sparseness, personalized recommendation, global feature, recommender systems

CLC Number:

中图分类号:TP391

ZHANG Ya, BAI Haiyan, MENG Xuyang. Personalized Literature Recommendation Algorithm Based on Log Mining[J]. Computer and Modernization, 2025, 0(12): 32-37.

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