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© 2007

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
Conference proceedings DaWaK 2007

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

Table of contents

  1. Data Warehousing and Data Mining

    1. Ladjel Bellatreche, Rokia Missaoui, Hamid Necir, Habiba Drias
      Pages 221-230
  2. Clustering

    1. Jiyeon Choo, Rachsuda Jiamthapthaksin, Chun-sheng Chen, Oner Ulvi Celepcikay, Christian Giusti, Christoph F. Eick
      Pages 231-240
    2. Yannis Marinakis, Magdalene Marinaki, Nikolaos Matsatsinis
      Pages 241-250
    3. MinTzu Wang, PingYu Hsu, K. C. Lin, ShiuannShuoh Chen
      Pages 251-261
    4. Haytham Elghazel, Khalid Benabdeslem, Alain Dussauchoy
      Pages 262-271
  3. Association Rules

    1. Show-Jane Yen, Yue-Shi Lee
      Pages 283-292
    2. Ghada Gasmi, Sadok Ben Yahia, Engelbert Mephu Nguifo, Slim Bouker
      Pages 293-302
  4. Healthcare and Biomedical Applications

    1. Alberto Freitas, Altamiro Costa-Pereira, Pavel Brazdil
      Pages 303-312
    2. Xiaodan Zhang, Xiaohua Hu, Jiali Xia, Xiaohua Zhou, Palakorn Achananuparp
      Pages 313-322
  5. Classification

    1. Mohammad Khabbaz, Kievan Kianmher, Mohammad Alshalalfa, Reda Alhajj
      Pages 334-344
    2. Manoranjan Dash, Vivekanand Gopalkrishnan
      Pages 345-354
  6. Partitioning

    1. Ronnie Alves, Orlando Belo, Joel Ribeiro
      Pages 375-384
    2. Zhidan Feng, Xiaowei Xu, Nurcan Yuruk, Thomas A. J. Schweiger
      Pages 385-396
    3. Zi Huang, Heng Tao Shen, Xiaofang Zhou, Jie Shao
      Pages 397-406
  7. Privacy and Crytography

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