Data Warehousing and Knowledge Discovery

The Second International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2000) was held in Greenwich, UK 4-6 September. DaWaK 2000 was a forum where researchers from data warehousing and knowledge discovery disciplines could exchange ideas on improving next generation decision support and data mining systems. The conference focused on the logical and physical design of data warehousing and knowledge discovery systems. The scope of the papers covered the most recent and relevant topics in the areas of data warehousing, multidimensional databases, OLAP, knowledge discovery and mining complex databases. These proceedings contain the technical papers selected for presentation at the conference. We received more than 90 papers from over 20 countries and the program committee finally selected 31 long papers and 11 short papers. The conference program included three invited talks, namely, "A Foolish Consistency: Technical Challenges in Consistency Management" by Professor Anthony Finkelstein, University College London, UK; "European Plan for Research in Data Warehousing and Knowledge Discovery" by Dr. Harald Sonnberger (Head of Unit A4, Eurostat, European Commission); and "Security in Data Warehousing" by Professor Bharat Bhargava, Purdue University, USA.

Inhalt

Data Warehouse Design.- The Design and Development of a Logical System for OLAP.- Applying Vertical Fragmentation Techniques in Logical Design of Multidimensional Databases.- Space-Efficient Data Cubes for Dynamic Environments.- On Making Data Warehouses Active.- Materialized Views.- Supporting Hot Spots with Materialized Views.- Evaluation of Materialized View Indexing in Data Warehousing Environments.- View Derivation Graph with Edge Fitting for Adaptive Data Warehousing.- On the Importance of Tuning in Incremental View Maintenance: An Experience Case Study.- Warehouse Data Creation and Maintenance.- BEDAWA - A Tool for Generating Sample Data for Data Warehouses.- DyDa: Dynamic Data Warehouse Maintenance in a Fully Concurrent Environment.- Scalable Maintenance of Multiple Interrelated Data Warehousing Systems.- View Maintenance for Hierarchical Semistructured Data.- Maintaining Horizontally Partitioned Warehouse Views.- Invited Talk.- Funding Research in Data Warehousing and Knowledge Discovery EPROS: The European Plan for Research in Official Statistics.- Warehouse Views Selection and Evolution.- Elimination of Redundant Views in Multidimensional Aggregates.- Data Cube Compression with QuantiCubes.- History-Driven View Synchronization.- A Logical Model for Data Warehouse Design and Evolution.- OLAP System Design and Query Analysis.- An Alternative Relational OLAP Modeling Approach.- Functional Dependencies in Controlling Sparsity of OLAP Cubes.- An OLAP-based Scalable Web Access Analysis Engine.- PROMISE: Predicting Query Behavior to Enable Predictive Caching Strategies for OLAP Systems.- OLAP Query Evaluation.- Supporting Online Queries in ROLAP.- Optimal Multidimensional Query Processing Using Tree Striping.- Enhancing Preprocessing in Data-Intensive Domains using Online-Analytical Processing.- Meta-queries - Computation and Evaluation.- Partitioning Algorithms for the Computation of Average Iceberg Queries.- Invited Talk.- Security in Data Warehousing.- Association Rules.- Mining of Association Rules in Text Databases Using Inverted Hashing and Pruning.- SQL Based Association Rule Mining Using Commercial RDBMS (IBM DB2 UDB EEE).- On Supporting Interactive Association Rule Mining.- Temporal Association Rules.- Discovering Temporal Patterns for Interval-based Events.- An Integrated Query and Mining System for Temporal Association Rules.- Mining Changes for Real-Life Applications.- AIM: Approximate Intelligent Matching for Time Series Data.- Mining Complex Databases.- Cofe: A Scalable Method for Feature Extraction from Complex Objects.- The Pruning Power: Theory and Heuristics for Mining Databases with Multiple k-Nearest-Neighbor Queries.- Data Mining Support in Database Management Systems.- Decision trees for probabilistic data.- Mining Frequent Binary Expressions.- A Fast Algorithm for Hierarchical Text Classification.- A Hybrid Technique for Data Mining on Balance-Sheet Data.- Mondou: Information Navigator with Visual Interface.- Vmhist: Efficient Multidimensional Histograms with Improved Accuracy.