Techniques for Data Mining

Techniques for Data Mining offers a comprehensive and application-driven introduction to one of the most dynamic fields in modern data science. Designed for students, educators, and professionals, this textbook presents foundational concepts and practical methods for uncovering patterns, relationships, and insights from complex datasets.

Beginning with the essentials—data preprocessing, warehousing, and integration—this book gradually explores advanced topics such as clustering, time-series analysis, graph mining, and frequent pattern discovery. Each chapter balances theory with real-world application, including hands-on strategies for educational environments, intelligent tutoring systems, adaptive learning platforms, and social network analysis.

Special attention is given to the growing role of data mining in personalised education, recommendation systems, and user modelling. With review questions and illustrative examples throughout, readers gain not just technical knowledge but a deeper understanding of how data mining enhances decision-making across fields.

Whether you’re working with transactional databases or designing adaptive learning systems, Techniques for Data Mining equips you with the tools and context needed to engage critically and creatively with today’s data-driven challenges.