MODERN APPROACHES OF DATA MINING: Theory and Practice discusses key concepts, theories, standards, methodologies, trends, challenges, and applications of data mining (DM) and knowledge discovery in databases (KDD) with an aim to uncover the hidden patterns from a large gamut of data. The DM techniques presented in this book have been inspired from the contributions of the diversified domain of researchers in the areas of artificial intelligence, pattern recognition, machine learning, database management systems, and decision sciences. The diverse field of real life applications and the potential initiative of leveraging these tools, techniques, and concepts against the data at hand to identify problems have been focused extensively with examples. Moreover, this book presents precise algorithmic descriptions of methods, including classical methods and their variants. In addition the recently developed novel methods along with their hybridization are also included. The concepts of web data mining is illustrated in a simple manner for easy understandability of the readers. Finally, this book gives in-depth descriptions of data mining applications in multiple-discipline including Intrusion detection.

Preface / Acknowledgements / Introduction / Association Rule Mining / Classification Techniques / Clustering Techniques / Regression Techniques / Advanced Data Mining Techniques / Web Data Mining / Data Mining Application to Intrusion Detection / Appendices / References / Index.

Under-Postgraduate Students, Professionals, Researchers & Industry