Abstract：Adoption of Data Mining Methods in the Discipline of Library and Information Science The purpose of this paper is to explore the recent trends of data mining method adoption in the library and information scienceLISdisciplineBibliographic records from the data mining and LIS fields were collected respectively from the Scopus databaseA dictionary of data mining method terms was constructed based on a rule-based textual analysisUsing the dictionarythis study investigated a range of prevalent data mining methods utilized in recent LIS studiesThe findings of this study reveal different areas of data mining methods employed in LISsuch as big datamachine learningtext mininginformation retrievaland dimension reductionThe study also confirms the recent popularity of machine learning techniques in LIS researchRetrieval and IndexingStudy mentioned information retrieval as a data mining method used in LISConsulting ServiceText mining and machine learning may be used to automatically answer inquiries or provide consultationCollection classificationMachine learning and other data mining methods may be used for automatic classification library resourcesThis study mainly explores the latest trends in the field of libraries and information scienceIt surveyed a variety of data mining methods commonly used in recent libraries and information studiesincluding big datamachine learningtext mininginformation retrieval and dimensionAmong themthe popularity of machine learning technology in libraries and information studies is particularly confirmed