Data Mining Applications for Empowering Knowledge Societies Hakikur Rahman Sustainable Development Networking Foundation (SDNF), Bangladesh InformatIon scIence reference Hershey • New York Director of Editorial Content: Managing Development Editor: Assistant Managing Development Editor: Assistant Development Editor: Senior Managing Editor: Managing Editor: Assistant Managing Editor: Copy Editor: Typesetter: Cover Design: Printed at: Kristin Klinger Kristin M Roth Jessica Thompson Deborah Yahnke Jennifer Neidig Jamie Snavely Carole Coulson Erin Meyer Sean Woznicki Lisa Tosheff Yurchak Printing Inc Published in the United States of America by Information Science Reference (an imprint of IGI Global) 701 E Chocolate Avenue, Suite 200 Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: cust@igi-global.com Web site: http://www.igi-global.com and in the United Kingdom by Information Science Reference (an imprint of IGI Global) Henrietta Street Covent Garden London WC2E 8LU Tel: 44 20 7240 0856 Fax: 44 20 7379 0609 Web site: http://www.eurospanbookstore.com Copyright © 2009 by IGI Global All rights reserved No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher Product or company names used in this set are for identification purposes only Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark Library of Congress Cataloging-in-Publication Data Data mining applications for empowering knowledge societies / Hakikur Rahman, editor p cm Summary: “This book presents an overview on the main issues of data mining, including its classification, regression, clustering, and ethical issues” Provided by publisher Includes bibliographical references and index ISBN 978-1-59904-657-0 (hardcover) ISBN 978-1-59904-659-4 (ebook) Data mining Knowledge management I Rahman, Hakikur, 1957QA76.9.D343D38226 2009 005.74 dc22 2008008466 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 set is original material The views expressed in this book are those of the authors, but not necessarily of the publisher If a library purchased a print copy of this publication, please go to http://www.igi-global.com/agreement for information on activating the library's complimentary electronic access to this publication Table of Contents Foreword xi Preface xii Acknowledgment xxii Section I Education and Research Chapter I Introduction to Data Mining Techniques via Multiple Criteria Optimization Approaches and Applications Yong Shi, University of the Chinese Academy of Sciences, China and University of Nebraska at Omaha, USA Yi Peng, University of Nebraska at Omaha, USA Gang Kou, University of Nebraska at Omaha, USA Zhengxin Chen, University of Nebraska at Omaha, USA Chapter II Making Decisions with Data: Using Computational Intelligence Within a Business Environment 26 Kevin Swingler, University of Stirling, Scotland David Cairns, University of Stirling, Scotland Chapter III Data Mining Association Rules for Making Knowledgeable Decisions 43 A.V Senthil Kumar, CMS College of Science and Commerce, India R S D Wahidabanu, Govt College of Engineering, India Section II Tools, Techniques, Methods Chapter IV Image Mining: Detecting Deforestation Patterns Through Satellites 55 Marcelino Pereira dos Santos Silva, Rio Grande Norte State University, Brazil Gilberto Câmara, National Institute for Space Research, Brazil Maria Isabel Sobral Escada, National Institute for Space Research, Brazil Chapter V Machine Learning and Web Mining: Methods and Applications in Societal Benefit Areas 76 Georgios Lappas, Technological Educational Institution of Western Macedonia, Kastoria Campus, Greece Chapter VI The Importance of Data Within Contemporary CRM 96 Diana Luck, London Metropolitan University, UK Chapter VII Mining Allocating Patterns in Investment Portfolios 110 Yanbo J Wang, University of Liverpool, UK Xinwei Zheng, University of Durham, UK Frans Coenen, University of Liverpool, UK Chapter VIII Application of Data Mining Algorithms for Measuring Performance Impact of Social Development Activities 136 Hakikur Rahman, Sustainable Development Networking Foundation (SDNF), Bangladesh Section III Applications of Data Mining Chapter IX Prospects and Scopes of Data Mining Applications in Society Development Activities 162 Hakikur Rahman, Sustainable Development Networking Foundation, Bangladesh Chapter X Business Data Warehouse: The Case of Wal-Mart 189 Indranil Bose, The University of Hong Kong, Hong Kong Lam Albert Kar Chun, The University of Hong Kong, Hong Kong Leung Vivien Wai Yue, The University of Hong Kong, Hong Kong Li Hoi Wan Ines, The University of Hong Kong, Hong Kong Wong Oi Ling Helen, The University of Hong Kong, Hong Kong Chapter XI Medical Applications of Nanotechnology in the Research Literature 199 Ronald N Kostoff, Office of Naval Research, USA Raymond G Koytcheff, Office of Naval Research, USA Clifford G.Y Lau, Institute for Defense Analyses, USA Chapter XII Early Warning System for SMEs as a Financial Risk Detector 221 Ali Serhan Koyuncugil, Capital Markets Board of Turkey, Turkey Nermin Ozgulbas, Baskent University, Turkey Chapter XIII What Role is “Business Intelligence” Playing in Developing Countries? A Picture of Brazilian Companies 241 Maira Petrini, Fundaỗóo Getulio Vargas, Brazil Marlei Pozzebon, HEC Montreal, Canada Chapter XIV Building an Environmental GIS Knowledge Infrastructure 262 Inya Nlenanya, Center for Transportation Research and Education, Iowa State University, USA Chapter XV The Application of Data Mining for Drought Monitoring and Prediction 280 Tsegaye Tadesse, National Drought Mitigation Center, University of Nebraska, USA Brian Wardlow, National Drought Mitigation Center, University of Nebraska, USA Michael J Hayes, National Drought Mitigation Center, University of Nebraska, USA Compilation of References 292 About the Contributors 325 Index 330 Detailed Table of Contents Foreword xi Preface xii Acknowledgment xxii Section I Education and Research Chapter I Introduction to Data Mining Techniques via Multiple Criteria Optimization Approaches and Applications Yong Shi, University of the Chinese Academy of Sciences, China and University of Nebraska at Omaha, USA Yi Peng, University of Nebraska at Omaha, USA Gang Kou, University of Nebraska at Omaha, USA Zhengxin Chen, University of Nebraska at Omaha, USA This chapter presents an overview of a series of multiple criteria optimization-based data mining methods that utilize multiple criteria programming to solve various data mining problems and outlines some research challenges At the same time, this chapter points out to several research opportunities for the data mining community Chapter II Making Decisions with Data: Using Computational Intelligence Within a Business Environment 26 Kevin Swingler, University of Stirling, Scotland David Cairns, University of Stirling, Scotland This chapter identifies important barriers to the successful application of computational intelligence techniques in a commercial environment and suggests a number of ways in which they may be overcome It further identifies a few key conceptual, cultural, and technical barriers and describes different ways in which they affect business users and computational intelligence practitioners This chapter aims to provide knowledgeable insight for its readers through outcome of a successful computational intelligence project Chapter III Data Mining Association Rules for Making Knowledgeable Decisions 43 A.V Senthil Kumar, CMS College of Science and Commerce, India R S D Wahidabanu, Govt College of Engineering, India This chapter describes two popular data mining techniques that are being used to explore frequent large itemsets in the database The first one is called closed directed graph approach where the algorithm scans the database once making a count on possible 2-itemsets from which only the 2-itemsets with a minimum support are used to form the closed directed graph and explores possible frequent large itemsets in the database In the second one, dynamic hashing algorithm where large 3-itemsets are generated at an earlier stage that reduces the size of the transaction database after trimming and thereby cost of later iterations will be reduced However, this chapter envisages that these techniques may help researchers not only to understand about generating frequent large itemsets, but also finding association rules among transactions within relational databases, and make knowledgeable decisions Section II Tools, Techniques, Methods Chapter IV Image Mining: Detecting Deforestation Patterns Through Satellites 55 Marcelino Pereira dos Santos Silva, Rio Grande Norte State University, Brazil Gilberto Câmara, National Institute for Space Research, Brazil Maria Isabel Sobral Escada, National Institute for Space Research, Brazil This chapter presents with relevant definitions on remote sensing and image mining domain, by referring to related work in this field and demonstrates the importance of appropriate tools and techniques to analyze satellite images and extract knowledge from this kind of data A case study, the Amazonia with deforestation problem is being discussed, and effort has been made to develop strategy to deal with challenges involving Earth observation resources The purpose is to present new approaches and research directions on remote sensing image mining, and demonstrates how to increase the analysis potential of such huge strategic data for the benefit of the researchers Chapter V Machine Learning and Web Mining: Methods and Applications in Societal Benefit Areas 76 Georgios Lappas, Technological Educational Institution of Western Macedonia, Kastoria Campus, Greece This chapter reviews contemporary researches on machine learning and Web mining methods that are related to areas of social benefit It further demonstrates that machine learning and web mining methods may provide intelligent Web services of social interest The chapter also discusses about the growing interest of researchers in recent days for using advanced computational methods, such as machine learning and Web mining, for better services to the public Chapter VI The Importance of Data Within Contemporary CRM 96 Diana Luck, London Metropolitan University, UK This chapter search for the importance of customer relationship management (CRM) in the product development and service elements as well as organizational structure and strategies, where data takes as the pivotal dimension around which the concept of CRM revolves in contemporary terms Subsequently it has tried to demonstrate how these processes are associated with data management, namely: data collection, data collation, data storage and data mining, and are becoming essential components of CRM in both theoretical and practical aspects Chapter VII Mining Allocating Patterns in Investment Portfolios 110 Yanbo J Wang, University of Liverpool, UK Xinwei Zheng, University of Durham, UK Frans Coenen, University of Liverpool, UK This chapter has introduced the concept of “one-sum” weighted association rules (WARs) and named such WARs as allocating patterns (ALPs) Here, an algorithm is being proposed to extract hidden and interesting ALPs from data The chapter further points out that ALPs can be applied in portfolio management, and modeling a collection of investment portfolios as a one-sum weighted transaction-database, ALPs can be applied to guide future investment activities Chapter VIII Application of Data Mining Algorithms for Measuring Performance Impact of Social Development Activities 136 Hakikur Rahman, Sustainable Development Networking Foundation (SDNF), Bangladesh This chapter focuses to data mining applications and their utilizations in devising performance-measuring tools for social development activities It has provided justifications to include data mining algorithm for establishing specifically derived monitoring and evaluation tools that may be used for various social development applications Specifically, this chapter gave in-depth analytical observations for establishing knowledge centers with a range of approaches and put forward a few research issues and challenges to transform the contemporary human society into a knowledge society Section III Applications of Data Mining Chapter IX Prospects and Scopes of Data Mining Applications in Society Development Activities 162 Hakikur Rahman, Sustainable Development Networking Foundation, Bangladesh Chapter IX focuses on a few areas of social development processes and put forwards hints on application of data mining tools, through which decision-making would be easier Subsequently, it has put forward potential areas of society development initiatives, where data mining applications can be incorporated The focus area may vary from basic social services, like education, health care, general commodities, tourism, and ecosystem management to advanced uses, like database tomography Chapter X Business Data Warehouse: The Case of Wal-Mart 189 Indranil Bose, The University of Hong Kong, Hong Kong Lam Albert Kar Chun, The University of Hong Kong, Hong Kong Leung Vivien Wai Yue, The University of Hong Kong, Hong Kong Li Hoi Wan Ines, The University of Hong Kong, Hong Kong Wong Oi Ling Helen, The University of Hong Kong, Hong Kong This chapter highlights on business data warehouse and discusses about the retailing giant Wal-Mart Here, the planning and implementation of the Wal-Mart data warehouse is being described and its integration with the operational systems is being discussed This chapter has also highlighted some of the problems that have been encountered during the development process of the data warehouse, and provided some future recommendations about Wal-Mart data warehouse Chapter XI Medical Applications of Nanotechnology in the Research Literature 199 Ronald N Kostoff, Office of Naval Research, USA Raymond G Koytcheff, Office of Naval Research, USA Clifford G.Y Lau, Institute for Defense Analyses, USA Chapter XI examines medical applications literatures that are associated with nanoscience and nanotechnology research For this research, authors have retrieved about 65000 nanotechnology records in 2005 from the Science Citation Index/ Social Science Citation Index (SCI/SSCI) using a comprehensive 300+ term query, and in this chapter they intend to facilitate the nanotechnology transition process by identifying the significant application areas Specifically, it has identified the main nanotechnology health applications from today’s vantage point, as well as the related science and infrastructure The medical applications were ascertained through a fuzzy clustering process, and metrics were generated using text mining to extract technical intelligence for specific medical applications/ applications groups Chapter XII Early Warning System for SMEs as a Financial Risk Detector 221 Ali Serhan Koyuncugil, Capital Markets Board of Turkey, Turkey Nermin Ozgulbas, Baskent University, Turkey This chapter introduces an early warning system for SMEs (SEWS) as a financial risk detector that is based on data mining During the development of an early warning system, it compiled a system in which qualitative and quantitative data about the requirements of enterprises are taken into consideration Moreover, an easy to understand, easy to interpret and easy to apply utilitarian model is targeted by discovering the implicit relationships between the data and the identification of effect level of every factor related to the system This chapter eventually shows the way of empowering knowledge society from SME’s point of view by designing an early warning system based on data mining ... Cataloging-in-Publication Data Data mining applications for empowering knowledge societies / Hakikur Rahman, editor p cm Summary: “This book presents an overview on the main issues of data mining, including.. .Data Mining Applications for Empowering Knowledge Societies Hakikur Rahman Sustainable Development Networking Foundation (SDNF), Bangladesh InformatIon scIence reference... and the use of data and information for empowering knowledge societies Most books of data mining deal with mere technology aspects, despite the diversified nature of its various applications along