Dynamic and Advanced Data Mining for Progressing Technological Development_ Innovations and Systemic Approaches [Ali & Xiang 2009-11-25](1).pdf

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Dynamic and Advanced
Data Mining for
Progressing Technological
Development:
Innovations and Systemic
Approaches
A B M Shawkat Ali
Central Queensland University, Australia
Yang Xiang
Central Queensland University, Australia
InformatIon scIence reference
Hershey • New York
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Library of Congress Cataloging-in-Publication Data
Dynamic and advanced data mining for progressing technological development :
innovations and systemic approaches / A.B.M. Shawkat Ali and Yang Xiang,
editors.
p. cm.
Summary: "This book discusses advances in modern data mining research in
today's rapidly growing global and technological environment"--Provided by
publisher.
Includes bibliographical references and index.
ISBN 978-1-60566-908-3 (hardcover) -- ISBN 978-1-60566-909-0 (ebook) 1.
Data mining. 2. Technological innovations. I. Shawkat Ali, A. B. M. II.
Xiang, Yang, 1975-
QA76.9.D343D956 2010
303.48'3--dc22
2009035155
British Cataloguing in Publication Data
A Cataloguing in Publication record for this book is available from the British Library.
All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the
authors, but not necessarily of the publisher.
Table of Contents
Preface
................................................................................................................................................. xv
Chapter 1
Data Mining Techniques for Web Personalization: Algorithms and Applications.................................. 1
Gulden Uchyigit, University of Brighton, UK
Chapter 2
Patterns Relevant to the Temporal Data-Context of an Alarm of Interest ............................................ 18
Savo Kordic, Edith Cowan University, Australia
Chiou Peng Lam, Edith Cowan University, Australia
Jitian Xiao, Edith Cowan University, Australia
Huaizhong Li, Wenzhou University, China
Chapter 3
ODARM: An Outlier Detection-Based Alert Reduction Model ........................................................... 40
Fu Xiao, Nanjing University, P.R. China
Xie Li, Nanjing University, P.R. China
Chapter 4
Concept-Based Mining Model .............................................................................................................. 57
Shady Shehata, University of Waterloo, Canada
Fakhri Karray, University of Waterloo, Canada
Mohamed Kamel, University of Waterloo, Canada
Chapter 5
Intrusion Detection Using Machine Learning: Past and Present .......................................................... 70
Mohammed M. Mazid, CQUniversity, Australia
A B M Shawkat Ali, CQUniversity, Australia
Kevin S. Tickle, CQUniversity, Australia
Chapter 6
A Re-Ranking Method of Search Results Based on Keyword and User Interest ............................... 108
Ming Xu, Hangzhou Dianzi University, P. R. China
Hong-Rong Yang, Hangzhou Dianzi University, P. R. China
Ning Zheng, Hangzhou Dianzi University, P. R. China
Chapter 7
On the Mining of Cointegrated Econometric Models......................................................................... 122
J. L. van Velsen, Dutch Ministry of Justice, Research and Documentation
Centre (WODC), The Netherlands
R. Choenni, Dutch Ministry of Justice, Research and Documentation Centre (WODC),
The Netherlands
Chapter 8
Spreading Activation Methods............................................................................................................ 136
Alexander Troussov, IBM, Ireland
Eugene Levner, Holon Institute of Technology and Bar-Ilan University, Israel
Cristian Bogdan, KTH – Royal Institute of Technology, Sweden
John Judge, IBM, Ireland
Dmitri Botvich, Waterford Institute of Technology, Ireland
Chapter 9
Pattern Discovery from Biological Data ............................................................................................. 168
Jesmin Nahar, Central Queensland University, Australia
Kevin S. Tickle, Central Queensland University, Australia
A B M Shawkat Ali, Central Queensland University, Australia
Chapter 10
Introduction to Clustering: Algorithms and Applications ................................................................... 224
Raymond Greenlaw, Armstrong Atlantic State University, USA
Sanpawat Kantabutra, Chiang Mai University, Thailand
Chapter 11
Financial Data Mining Using Flexible ICA-GARCH Models ........................................................... 255
Philip L.H. Yu, The University of Hong Kong, Hong Kong
Edmond H.C. Wu, The Hong Kong Polytechnic University, Hong Kong
W.K. Li, The University of Hong Kong, Hong Kong
Chapter 12
Machine Learning Techniques for Network Intrusion Detection ....................................................... 273
Tich Phuoc Tran, University of Technology, Australia
Pohsiang Tsai, University of Technology, Australia
Tony Jan, University of Technology, Australia
Xiangjian He, University of Technology, Australia

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