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Advances in Data Warehousing and Mining (ADWM) Book Series

DOI: 10.4018/ADWM
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Description

The Advances in Data Warehousing and Mining (ADWM) Book Series aims to publish and disseminate knowledge on an international basis in the areas of data warehousing and data mining. The book series provides a highly regarded outlet for the most emerging research in the field and seeks to bridge underrepresented themes within the data warehousing and mining discipline.

The Advances in Data Warehousing and Mining (ADWM) Book Series serves to provide a continuous forum for state-of-the-art developments and research, as well as current innovative activities in data warehousing and mining. In contrast to other book series, the ADWM focuses on the integration between the fields of data warehousing and data mining, with emphasize on the applicability to real world problems.  ADWM is targeted at both academic researchers and practicing IT professionals.

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Mission

The Advances in Data Warehousing and Mining (ADWM) Book Series aims to publish and disseminate knowledge on an international basis in the areas of data warehousing and data mining, and focuses on the integration between the fields of data warehousing and data mining, with emphasize on the applicability to real world problems. ADWM endeavors to further research in this discipline and emphasize breaking principles and models.
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Topics Covered

ADWM is devoted to the publications of high quality books on theoretical developments and practical applications in data warehousing and data mining. Original research books, state-of-the-art reviews, and technical notes are invited for publications. The book series accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to books focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving data.Topics of interest to the series include, but are not limited to, the following areas:
  • Data models
  • Data structures
  • Design
  • Data warehousing process
  • Online analytical process
  • Tools and languages
  • Data dart and practical issues
  • Data mining methods
  • Algorithms
  • Mining databases
  • Knowledge discovery process
  • Tools and languages and applications issues
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    Editorial Advisory Board

    Advances in Data Warehousing and Mining (ADWM) Book SeriesEditor-in-Chief: David Taniar, Monash University, AustraliaAssociate Editors: Xiaohua Hu, Drexel University, USA Wenny Rahayu, La Trobe University, AustraliaInternational Editorial Advisory Board: Hussein Abbass, University of New South Wales, Australia Mafruz Zaman Ashrafi, Institute for Infocomm Research, Singapore Jérôme Darmont, University of Lyon 2, France Lixin Fu, University of North Carolina at Greensboro, USA Lance Chun Che Fung, Murdoch University, Australia Stephan Kudyba, New Jersey Institute of Technology, USA Zongmin Ma, Northeastern University, China Anthony Scime, State University of New York College at Brockport, USA Robert Wrembel, Poznan University of Technology, Poland Xingquan Zhu, Florida Atlantic University, USA
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    Author(s)/Editor(s) Biography

    David Taniar
    David Taniar received a PhD degree in databases from Victoria University (Australia, 1997). He 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 in 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).
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