Applied Data Mining

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest advances in newly emerging information services. It explores the extension of well-studied algorithms and approaches into these new research arenas.

Table of Contents

Part I: Fundamentals
Chapter 1: Introduction
Chapter 2: Mathematical Foundations
Chapter 3: Data Preparation
Chapter 4: Clustering Analysis
Chapter 5: Classification
Chapter 6: Frequent Pattern Mining

Part II: Advanced Data Mining
Chapter 7: Advanced Clustering Analysis
Chapter 8: Multi-Label Classification
Chapter 9: Privacy Preserving in Data Mining

Part III: Emerging Applications
Chapter 10: Data Stream
Chapter 11: Recommendation Systems
Chapter 12: Social Tagging Systems