Tóm tắt nội dung

It surveys a wide range of methodologies, including Bayesian data mining, feature selection, rough set approaches, and text mining, through contributions from numerous international experts. The book examines core operations in data mining such as predictive modeling, clustering, link analysis, and anomaly detection, highlighting both opportunities for extracting insights from large datasets and the technical challenges involved. It also addresses practical issues like missing data, distributed data mining, and ethical concerns in applying mining technologies. Case studies in areas such as healthcare, banking performance, and human resource systems illustrate how data mining is used in diverse domains. Designed for researchers and practitioners, the work provides a multidisciplinary perspective on the field’s state of the art and future trends. Overall, it serves as both a reference and exploratory guide to advanced data mining concepts and challenges