E-grāmata: Data Warehousing and Knowledge Discovery: 5th International Conference, DaWaK 2003, Prague, Czech Republic, September 3-5,2003, Proceedings

Invited Talk.- XML for Data Warehousing Chances and Challenges.- Data
Cubes and Queries.- CPM: A Cube Presentation Model for OLAP.- Computation of
Sparse Data Cubes with Constraints.- Answering Joint Queries from Multiple
Aggregate OLAP Databases.- An Approach to Enabling Spatial OLAP by
Aggregating on Spatial Hierarchy.- Multidimensional Data Model.- A
Multidimensional Aggregation Object (MAO) Framework for Computing
Distributive Aggregations.- The GMD Data Model for Multidimensional
Information: A Brief Introduction.- An Application of Case-Based Reasoning in
Multidimensional Database Architecture.- Web Warehousing.- MetaCube XTM: A
Multidimensional Metadata Approach for Semantic Web Warehousing Systems.-
Designing Web Warehouses from XML Schemas.- Building XML Data Warehouse Based
on Frequent Patterns in User Queries.- Change Detection.- A Temporal Study of
Data Sources to Load a Corporate Data Warehouse.- Automatic Detection of
Structural Changes in Data Warehouses.- Performance Tests in Data Warehousing
ETLM Process for Detection of Changes in Data Origin.- Web Mining and
Association Rule.- Recent Developments in Web Usage Mining Research.-
Parallel Vector Computing Technique for Discovering Communities on the Very
Large Scale Web Graph.- Association Rules and Decision Trees.- Ordinal
Association Rules towards Association Rules.- Rough Set Based Decision Tree
Model for Classification.- Inference Based Classifier: Efficient Construction
of Decision Trees for Sparse Categorical Attributes.- Generating Effective
Classifiers with Supervised Learning of Genetic Programming.- Clustering I.-
Clustering by Regression Analysis.- Handling Large Workloads by Profiling and
Clustering.- Incremental OPTICS: Efficient Computation of Updates in a
Hierarchical Cluster Ordering.- Clustering II.- On Complementarity of Cluster
and Outlier Detection Schemes.- Cluster Validity Using Support Vector
Machines.- FSSM: Fast Construction of the Optimized Segment Support Map.-
Association Rule Mining.- Using a Connectionist Approach for Enhancing Domain
Ontologies: Self-Organizing Word Category Maps Revisited.- Parameterless Data
Compression and Noise Filtering Using Association Rule Mining.- Performance
Evaluation of SQL-OR Variants for Association Rule Mining.- Data Analysis and
Discovery.- A Distance-Based Approach to Find Interesting Patterns.-
Similarity Search in Structured Data.- Ontologies and Improving Data
Quality.- Using an Interest Ontology for Improved Support in Rule Mining.-
Fraud Formalization and Detection.- Combining Noise Correction with Feature
Selection.- Queries and Data Patterns.- Pre-computing Approximate
Hierarchical Range Queries in a Tree-Like Histogram.- Comprehensive Log
Compression with Frequent Patterns.- Non-recursive Generation of Frequent
K-itemsets from Frequent Pattern Tree Representations.- Improving Database
Query Engine.- A New Computation Model for Rough Set Theory Based on Database
Systems.- Computing SQL Queries with Boolean Aggregates.- Fighting Redundancy
in SQL.- Sampling and Vector Classification.- On-the-fly VS Materialized
Sampling and Heuristics.- Incremental and Decremental Proximal Support Vector
Classification using Decay Coefficients.