XML Data Mining: Models, Methods, and Applications
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XML Data Mining: Models, Methods, and Applications

Andrea Tagarelli (University of Calabria, Italy)
Release Date: November, 2011|Copyright: © 2012 |Pages: 538
DOI: 10.4018/978-1-61350-356-0
ISBN13: 9781613503560|ISBN10: 1613503563|EISBN13: 9781613503577
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Description & Coverage
Description:

The widespread use of XML in business and scientific databases has prompted the development of methodologies, techniques, and systems for effectively managing and analyzing XML data. This has increasingly attracted the attention of different research communities, including database, information retrieval, pattern recognition, and machine learning, from which several proposals have been offered to address problems in XML data management and knowledge discovery.

XML Data Mining: Models, Methods, and Applications aims to collect knowledge from experts of database, information retrieval, machine learning, and knowledge management communities in developing models, methods, and systems for XML data mining. This book addresses key issues and challenges in XML data mining, offering insights into the various existing solutions and best practices for modeling, processing, analyzing XML data, and for evaluating performance of XML data mining algorithms and systems.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Approximate Matching of XML Documents and Schemas
  • Association Rule Mining of XML Data
  • Classification of XML Data
  • Clustering of XML Data
  • Domain-specific XML Mining Applications: Credit Risk Assessment, Social Network User Modeling of Geographical Maps, P2P systems
  • Frequent Pattern Discovery of XML Data
  • Mining of Evolving XML Data Streams
  • Mining of Uncertain XML Data
  • Semantics-aware Mining of XML Data
  • XML Mining for Semantic Web
  • XML Models for Data Mining
  • XML Similarity Search and Detection
Reviews and Testimonials

A very useful resource for advanced students and professionals. Summing Up: Recommended. Upper-division undergraduates and above.

– H. Levkowitz, University of Massachusetts, CHOICE, May 2012

I am confident that this timely volume will be the go-to reference for finding the latest methods and developments in XML data mining. It will be an invaluable resource for students, researchers, and practitioners in the field.

– Mohammed J. Zaki, Rensselaer Polytechnic Institute, USA

Each chapter is set out as a scholarly article, with an abstract, details and examples of the research question addressed, conclusions and proposals for future research, as well as a detailed bibliography. The book also has a detailed and very useful index. This is a technical volume targeted at researchers, computer scientists, developers and other practitioners working with XML data mining and related fields, such as web mining, information retrieval and knowledge management.

– Catherine Gilbert, Parliament of Australia Library. The Australian Library Journal, 62(3).
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Editor/Author Biographies
Andrea Tagarelli is an Assistant Professor of Computer Science with the Department of Electronics, Computer and Systems Sciences, University of Calabria, Italy. He graduated in Computer Engineering, in 2001, and obtained his Ph.D. in Computer and Systems Engineering, in 2006. He was visiting researcher at the Department of Computer Science & Engineering, University of Minnesota at Minneapolis, USA. His research interests include topics in knowledge discovery and text/data mining, information extraction, Web and semistructured data management, spatio-temporal databases, and bioinformatics. On these topics, he has coauthored journal articles, conference papers, and book chapters and developed practical software tools. He has served as a reviewer as well as a member of program committee for leading journals and conferences in the fields of databases and data mining, information systems, knowledge and data management, and artificial intelligence. He has been a SIAM member since 2008 and an ACM member since 2009.
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Editorial Review Board
  • Andrea Tagarelli, University of Calabria, Italy
  • Sourav S. Bhowmick, Nanyang Technological University, Singapore
  • Ludovic Denoyer, University “Pierre and Marie Curie”, Paris, France
  • Mounia Lalmas, University of Glasgow, UK
  • Christos Makris, University of Patras, Greece
  • Richi Nayak, Queensland University of Technology, Brisbane, Australia
  • Dan Simovici, University of Massachusetts at Boston, USA
  • Domenico Ursino, Mediterranea University of Reggio Calabria, Italy