Data Warehousing and Knowledge Discovery

9th International Conference, DaWaK 2007, Regensburg Germany, September 3-7, 2007. Proceedings

  • Editors
  • Il Yeal Song
  • Johann Eder
  • Tho Manh Nguyen

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4654)

Table of contents

  1. Front Matter
  2. Data Warehouse Architecture

    1. Cécile Favre, Fadila Bentayeb, Omar Boussaid
      Pages 13-22
    2. George Papastefanatos, Panos Vassiliadis, Alkis Simitsis, Yannis Vassiliou
      Pages 23-33
  3. Data Warehouse Quality

    1. Marko Banek, Boris Vrdoljak, A. Min Tjoa, Zoran Skočir
      Pages 45-54
    2. Wugang Xu, Dimitri Theodoratos, Calisto Zuzarte, Xiaoying Wu, Vincent Oria
      Pages 55-65
  4. Multidimensional Database

    1. Salvatore Orlando, Renzo Orsini, Alessandra Raffaetà, Alessandro Roncato, Claudio Silvestri
      Pages 66-77
    2. Rong She, Ke Wang, Ada Waichee Fu, Yabo Xu
      Pages 78-88
    3. Guillaume Cabanac, Max Chevalier, Franck Ravat, Olivier Teste
      Pages 89-98
  5. Data Warehouse and OLAP

    1. Oscar Romero, Alberto Abelló
      Pages 99-110
    2. Svetlana Mansmann, Thomas Neumuth, Marc H. Scholl
      Pages 111-122
    3. Véronique Cariou, Jérôme Cubillé, Christian Derquenne, Sabine Goutier, Françoise Guisnel, Henri Klajnmic
      Pages 123-134
    4. Sébastien Nedjar, Alain Casali, Rosine Cicchetti, Lotfi Lakhal
      Pages 135-144
  6. Query Optimization

    1. Apostolos N. Papadopoulos, Apostolos Lyritsis, Alexandros Nanopoulos, Yannis Manolopoulos
      Pages 145-156
    2. Nittaya Kerdprasop, Kittisak Kerdprasop
      Pages 157-169
    3. Fangling Leng, Yubin Bao, Daling Wang, Ge Yu
      Pages 170-180
  7. Data Warehousing and Data Mining

About these proceedings

Introduction

Data Warehousing and Knowledge Discovery have been widely accepted as key te- nologies for enterprises and organizations to improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision-making process, the data to be processed become more and more complex in both structure and semantics. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data constitutes the reality check for research in the area. During the past few years, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has become one of the most important international scientific events bringing together researchers, developers and practitioners. The DaWaK conferences served as a prominent forum for discussing latest research issues and experiences in developing and deploying data warehousing and knowledge d- covery systems, applications, and solutions. This year’s conference, the Ninth Inter- tional Conference on Data Warehousing and Knowledge Discovery (DaWaK 2007), built on this tradition of facilitating the cross-disciplinary exchange of ideas, expe- ence and potential research directions. DaWaK 2007 sought to disseminate innovative principles, methods, algorithms and solutions to challenging problems faced in the development of data warehousing, knowledge discovery and data mining applications.

Keywords

LA OLAP On-Line Analytical Processing classification data warehouse knowledge discovery ontology service-oriented computing warehousing

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-74553-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-74552-5
  • Online ISBN 978-3-540-74553-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book