Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments

Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments

David Taniar, Laura Irina Rusu
Release Date: December, 2009|Copyright: © 2010 |Pages: 448
DOI: 10.4018/978-1-60566-717-1
ISBN13: 9781605667171|ISBN10: 160566717X|EISBN13: 9781605667188
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Description & Coverage
Description:

Organizations rely on data mining and warehousing technologies to store, integrate, query, and analyze essential data.

Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments discusses developments in data mining and warehousing as well as techniques for successful implementation. Contributions investigate theoretical queries along with real-world applications, providing a useful foundation for academicians and practitioners to research new techniques and methodologies.

Coverage:

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

  • Cross-selling using data mining techniques
  • Data Warehousing and Data Mining
  • Elasticity of spatial data
  • Gene Expression Data
  • Heterogeneous data warehouse schemas
  • Medical Document Clustering
  • Mining temporal relational patterns
  • OLAP manipulations
  • Ranking systems in relation to data mining
  • Sequential patterns in relation to pattern mining
  • Vertical fragmentation using data-mining techniques
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Editor/Author Biographies
David Taniar received his PhD in Databases from Victoria University (Australia, 1997) and is now a Senior Lecturer at Monash University (Australia). He has published more than 100 research articles and edited a number of books in the Web technology series. He is on the editorial board of a number of international journals, including Data Warehousing and Mining, Business Intelligence and Data Mining, Mobile Information Systems, Mobile Multimedia, Web Information Systems, and Web and Grid Services. He has been elected as a Fellow of the Institute for Management of Information Systems (UK).
Laura Irina Rusu has completed her PhD in 2008 at La Trobe University, Australia, with a thesis on XML data warehousing and mining. Before that, she received a Master in Quantitative Economy degree (1997) and a Bachelor in Computer Science degree (1996), both from the Academy of Economic Sciences - Bucharest, Romania. Currently she is a Postdoctoral Research Fellow at La Trobe University, and her research interests are on dynamic XML data warehousing and mining, partitioning techniques for XML warehouses, and data migration to domain-specific XML standards.
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Editorial Advisory Board
  • Frank Dehne, Carleton University, Canada
  • Ada Wai-Chee Fu, Chinese University of Hong Kong, Hong Kong
  • Ee-Peng Lim, Singapore Management University, Singapore
  • Feng Ling, Tsinghua University, China
  • Graeme Shanks, The University of Melbourne, Australia
  • Chengqi Zhang, University of Technology, Australia