Preface
The data era is here. It provides a wealth of opportunities, but also poses
challenges for the effective and effi cient utilization of the huge data. Data
mining research is necessary to derive useful information from large data.
The book reviews applied data mining from theoretical basis to practical
applications.
The book consists of three main parts: Fundamentals, Advanced
Data Mining, and Emerging Applications. In the fi rst part, the authors
fi rst introduce and review the fundamental concepts and mathematical
models which are commonly used in data mining.There are fi ve chapters
in this section, which lay a solid base and prepare the necessary skills and
approaches for further understanding the remaining parts of the book. The
second part comprises three chapters and addresses the topics of advanced
clustering, multi-label classifi cation, and privacy preserving, which are
all hot topics in applied data mining. In the fi nal part, the authors present
some recent emerging applications of applied data mining, i.e., data
stream,recommender systems, and social tagging annotation systems.This
part introduces the contents in a sequence of theoretical background, state-
of-the-art techniques, application cases, and future research directions.
This book combines the fundamental concepts, models, and algorithms
in the data mining domain together, to serve as a reference for researchers
and practitioners from as diverse backgrounds as computer science,
machine learning, information systems, artifi cial intelligence, statistics,
operational science, business intelligence as well as social science disciplines.
Furthermore, this book provides a compilation and summarization for
disseminating and reviewing the recent emerging advances in a variety of
data mining application arenas, such as advanced data mining, analytics,
internet computing, recommender systems as well as social computing
and applied informatics from the perspective of developmental practice
for emerging research and practical applications. This book will also be
useful as a textbook for postgraduate students and senior undergraduate
students in related areas.
vi Applied Data Mining
This book features the following topics:
• Systematically presents and discusses the mathematical background
and representative algorithms for data mining, information retrieval,
and internet computing.
• Thoroughly reviews the related studies and outcomes conducted on
the addressed topics.
• Substantially demonstrates various important applications in the
areas of classical data mining, advanced data mining, and emerging
research topics such as stream data mining, recommender systems,
social computing.
• Heuristically outlines the open research issues of interdisciplinary
research topics, and identifi es several future research directions that
readers may be interested in.
April 2013 Guandong Xu
Yu Zong
Zhenglu Yang
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.