Data Warehousing and Knowledge Discovery

1. Front Matter

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2. Data Warehouse Architecture

   1. A Hilbert Space Compression Architecture for Data Warehouse Environments

      • Todd Eavis, David Cueva

      Pages 1-12

   2. Evolution of Data Warehouses’ Optimization: A Workload Perspective

      • Cécile Favre, Fadila Bentayeb, Omar Boussaid

      Pages 13-22

   3. What-If Analysis for Data Warehouse Evolution

      • George Papastefanatos, Panos Vassiliadis, Alkis Simitsis, Yannis Vassiliou

      Pages 23-33

3. Data Warehouse Quality

   1. An Extensible Metadata Framework for Data Quality Assessment of Composite Structures

      • José Farinha, Maria José Trigueiros

      Pages 34-44

   2. Automating the Schema Matching Process for Heterogeneous Data Warehouses

      • Marko Banek, Boris Vrdoljak, A. Min Tjoa, Zoran Skočir

      Pages 45-54

   3. A Dynamic View Materialization Scheme for Sequences of Query and Update Statements

      • Wugang Xu, Dimitri Theodoratos, Calisto Zuzarte, Xiaoying Wu, Vincent Oria

      Pages 55-65

4. Multidimensional Database

   1. Spatio-temporal Aggregations in Trajectory Data Warehouses

      • Salvatore Orlando, Renzo Orsini, Alessandra Raffaetà, Alessandro Roncato, Claudio Silvestri

      Pages 66-77

   2. Computing Join Aggregates over Private Tables

      • Rong She, Ke Wang, Ada Waichee Fu, Yabo Xu

      Pages 78-88

   3. An Annotation Management System for Multidimensional Databases

      • Guillaume Cabanac, Max Chevalier, Franck Ravat, Olivier Teste

      Pages 89-98

5. Data Warehouse and OLAP

   1. On the Need of a Reference Algebra for OLAP

      • Oscar Romero, Alberto Abelló

      Pages 99-110

   2. OLAP Technology for Business Process Intelligence: Challenges and Solutions

      • Svetlana Mansmann, Thomas Neumuth, Marc H. Scholl

      Pages 111-122

   3. Built-In Indicators to Automatically Detect Interesting Cells in a Cube

      • Véronique Cariou, Jérôme Cubillé, Christian Derquenne, Sabine Goutier, Françoise Guisnel, Henri Klajnmic

      Pages 123-134

   4. Emerging Cubes for Trends Analysis in Olap Databases

      • Sébastien Nedjar, Alain Casali, Rosine Cicchetti, Lotfi Lakhal

      Pages 135-144

6. Query Optimization

   1. Domination Mining and Querying

      • Apostolos N. Papadopoulos, Apostolos Lyritsis, Alexandros Nanopoulos, Yannis Manolopoulos

      Pages 145-156

   2. Semantic Knowledge Integration to Support Inductive Query Optimization

      • Nittaya Kerdprasop, Kittisak Kerdprasop

      Pages 157-169

   3. A Clustered Dwarf Structure to Speed Up Queries on Data Cubes

      • Fangling Leng, Yubin Bao, Daling Wang, Ge Yu

      Pages 170-180

7. Data Warehousing and Data Mining

   1. An OLAM-Based Framework for Complex Knowledge Pattern Discovery in Distributed-and-Heterogeneous-Data-Sources and Cooperative Information Systems

      • Alfredo Cuzzocrea

      Pages 181-198

   2. Integrating Clustering Data Mining into the Multidimensional Modeling of Data Warehouses with UML Profiles

      • Jose Zubcoff, Jesús Pardillo, Juan Trujillo

      Pages 199-208

   3. A UML Profile for Representing Business Object States in a Data Warehouse

      • Veronika Stefanov, Beate List

      Pages 209-220

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.

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

Policies and ethics