Predictive analytic of library patron behavior

This paper proposed the predictive analytics on big data analytics framework to identify and predict the library patron behaviour at Khon Kaen University Library (KKU Library). The research findings showed that big data analytics with additional machine learning algorithms using gradient boosting tree can be used as an effective tool to characterise patron behavior. KKU Library has continued to gain new insights into its patrons and their library access behaviour and better predictive capabilities, which enable resources to be optimised and service delivery to be more effective.