抄録
As one of the most important technologies in the information age, data mining is increasingly becoming a core tool driving scientific research and the intelligent transformation of industries. This paper systematically reviews the complete process and key technological system of data mining, with a particular focus on core methods such as data preprocessing, classification and clustering analysis, association rule mining, regression analysis, anomaly detection, time series analysis, text mining, and graph data mining. It discusses the applicable scenarios and algorithmic mechanisms of each technique, examines standards for evaluating model reliability and interpretability, and explores effective forms of knowledge representation. Furthermore, through practical case studies, it illustrates the diverse application pathways of data mining outcomes in business decision-making, scientific research, and social governance through practical case studies. This study aims to provide researchers and practitioners with a comprehensive, systematic, and practically valuable reference framework to facilitate the effective understanding and application of data mining technologies, ultimately promoting the transformation of data into knowledge and knowledge into value.
