Applied Data Mining

Applied Data Mining

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Summary

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

FUNDAMENTALS
Introduction
Mathematical Foundations
Data Preparation
Cluster Analysis
Classification
Frequent Pattern Mining

ADVANCED DATA MINING
Advanced Clustering Analysis
Privacy Preserving in Data Mining
Data Stream

EMERGING APPLICATIONS
Web Clustering and Web Community
Recommender Systems
Data Mining in Social Tagging Systems
Social Network Mining

Author Bio(s)

Dr. Guandong Xu , Centre for Applied Informatics, School of Engineering and Science, Victoria University, Australia

Prof. Yu Zong, Department of Information and Engineering, West Anhui University, China

Dr. Zhenglu Yang, Institute of Industrial Science, Tokyo, Japan

 
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