Machine Learning Offers Opportunities To Advance Library Services

This article discusses the use of machine learning and natural language processing to analyze library chat reference transcripts. The study aimed to develop a model that could predict if a chat question was reference or non-reference. The results showed that both random forest and gradient boosting models performed well in precision, recall, and accuracy, with the random forest model being more efficient. This could be beneficial for high volume library chat services in quickly filtering chat queries.