Bayesian algorithm in library information social services research
Kuotai Tang, Chujun Huang · 2023
The application of Library information service in social network is the concern of netizens, and how to develop intelligent recommendation service is an important topic for managers. In order to solve this problem, this paper uses "The Five Laws of Library Science" to build a model of influencing factors of library information application social network. A total of 302 valid questionnaires were collected. Reliability test was conducted after data preprocessing. Cronbach alpha=0.873 (>0.8), validity test KMO=0.799 (>0.7), indicating that the model has better quality. Then, the Bayesian network algorithm selected "library information management, social software application, user interest track" as the target variable, and "User reading needs, use of social software, user usage scenarios" as the dependent variable. The results show that: (1) We Chat users have high reading demand; (2) Data tracking is allowed when the demand is met; (3) We Chat users have a high demand for library information; (4) Consulting and reading services make the experience better; (5) It is more necessary to use intelligent recommendation in marketing; (6) Preferred learners focus on content sharing and timeliness. The research results help managers understand the application of personalized library and information service recommendation, so as to better meet the needs of users.