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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.

Applied Data Mining

POST SECONDARY FOUR YEAR

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APPLIED DATA MINING

Duration

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Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Preface.
Contents.
Fundamentals.
1: Introduction.
2: Mathematical Foundations.
3: Data Preparation.
4: Clustering Analysis.
5: Classification.
6: Frequent Pattern Mining.
Advanced Data Mining.
7: Advanced Clustering Analysis.
8: Multi-Label Classification.
9: Privacy Preserving in Data Mining.
Emerging Applications.
10: Data Stream.
11: Recommendation Systems.
12: Social Tagging Systems.

Applied Data Mining.css-1p8rvzy{position:absolute;padding-left:8px;}

Applied Data Mining