Construction of Personalized Service System of Digital Resource Library Based on Artificial Intelligence

Personalized service is a targeted initiative for digital resource libraries to improve the quality of service and better play the function of culture and education. This paper proposes a digital book personalized recommendation algorithm based on artificial intelligence technology. After acquiring the borrowing data and pre-processing, the reader’s portrait is visualized with factor analysis and cluster analysis methods respectively. The traditional Slopeone algorithm is weighted and the collaborative filtering algorithm is improved. Combine the user profile with collaborative filtering to realize the personalized recommendation of digital books. User similarity calculates four types of readers such as pragmatic, youthful, recreational and curious. This paper’s algorithm outperforms CFRA and RABC algorithms under each parameter, with the highest recommendation accuracy and novelty, and realizes personalized library services.