Exploration of usage behavioral model construction for university library electronic resources from Deep Learning Multilayer perceptron

The majority of this study is to use the MLP, Multilayer perceptron, operation method of deep learning to predict the reader's behavior intention and the quality of use behavior generated from the electronic library service quality of the university library. A questionnaire was built based on the quality of network electronic resource services and the theoretical structure of UTAUT. Combining the public and private university students who are four-year universities and two-year masters in Taiwan, there were 1,206 questionnaires issued and 1,071 valid questionnaires were collected. The predicted results of the MLP were based on the Pearson coefficient with the calculated results of the SPSS statistical method. It was found that the calculation method of AI can accurately predict the usage behavior of 90.75% or more. According to the practice, MLP regression models can be applied to the construction of library electronic resources, such as the addition of electronic multimedia resources, or the choice of books in the future. You can use this type of deep learning model to quickly predict and make decisions.