Successes and New Directions in Data Mining [Messeglia, Poncelet & Teisseire 2007-11-01](1).pdf

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Successes and New
Directions in Data Mining
Florent Masseglia
Project AxIS-INRIA, France
Pascal Poncelet
Ecole des Mines d'Ales, France
Maguelonne Teisseire
Universite Montpellier, France
InformatIon scIence reference
Hershey • New York
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Library of Congress Cataloging-in-Publication Data
Successes and new directions in data mining / Florent Messeglia, Pascal Poncelet & Maguelonne Teisseire, editors.
p. cm.
Summary: “This book addresses existing solutions for data mining, with particular emphasis on potential real-world applications. It
captures defining research on topics such as fuzzy set theory, clustering algorithms, semi-supervised clustering, modeling and managing
data mining patterns, and sequence motif mining”--Provided by publisher.
Includes bibliographical references and index.
ISBN 978-1-59904-645-7 (hardcover) -- ISBN 978-1-59904-647-1 (ebook)
1. Data mining. I. Masseglia, Florent. II. Poncelet, Pascal. III. Teisseire, Maguelonne.
QA76.9.D343S6853 2007
005’74--dc22
2007023451
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All work contributed to this book set is new, previously-unpublished material.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 www.igi-global.com/reference/assets/IGR-eAccess-agreement.pdf for
information on activating the library's complimentary electronic access to this publication.
Table of Contents
Preface
.................................................................................................................................................. xi
Acknowledgment
............................................................................................................................... xvi
Chapter I
Why Fuzzy Set Theory is Useful in Data Mining /
Eyke Hüllermeier ...................................................
1
Chapter II
SeqPAM: A Sequence Clustering Algorithm for Web Personalization /
Pradeep Kumar, Raju S. Bapi, and P. Radha Krishna ..........................................................................
17
Chapter III
Using Mined Patterns for XML Query Answering /
Elena Baralis, Paolo Garza,
Elisa Quintarelli, and Letizia Tanca .....................................................................................................
39
Chapter IV
On the Usage of Structural Information in Constrained Semi-Supervised Clustering
of XML Domcuments /
Eduardo Bezerra, Geraldo Xexéo, and Marta Mattoso .................................
67
Chapter V
Modeling and Managing Heterogeneous Patterns: The PSYCHO Experience /
Anna Maddalena and Barbara Catania ...............................................................................................
87
Chapter VI
Deterministic Motif Mining in Protein Databases /
Pedro Gabriel Ferreira and Paulo Jorge Azevedo .............................................................................
116
Chapter VII
Data Mining and Knowledge Discovery in Metabolomics /
Christian Baumgartner and Armin Graber ........................................................................................
141
Chapter VIII
Handling Local Patterns in Collaborative Structuring /
Ingo Mierswa, Katharina Morik, and Michael Wurst.........................................................................
167
Chapter IX
Pattern Mining and Clustering on Image Databases /
Marinette Bouet, Pierre Gançarski, Marie-Aude Aufaure, and Omar Boussaïd ................................
187
Chapter X
Semantic Integration and Knowledge Discovery for Environmental Research /
Zhiyuan Chen, Aryya Gangopadhyay, George Karabatis, Michael McGuire, and Claire Welty .......
213
Chapter XI
Visualizing Multi Dimensional Data /
César García-Osorio and Colin Fyfe .................................................................................................
236
Chapter XII
Privacy Preserving Data Mining, Concepts, Techniques, and Evaluation Methodologies /
Igor Nai Fovino...................................................................................................................................
277
Chapter XIII
Mining Data-Streams /Hanady
Abdulsalam, David B. Skillicorn, and Pat Martin ............................
302
Compilation of References
.............................................................................................................. 325
About the Contributors
................................................................................................................... 361
Index
................................................................................................................................................... 367

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