9.00 –
10.00 Invited Talk
XML for Datawarehouses
Chances and Challenges
10.00 – 10.30 Coffee Break
Session
1: Data Cubes and Queries
10.30 – 12.30
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
12.30 – 14.00 Lunch
Session 2A: Multidimensional
Data Model
14.00 – 15.30
A Multidimensional Aggregation Object Framework For Computing
Distributive Aggregations
The GMD Data Model for Multidimensional
Information
An Application of Case-Based Reasoning in Multidimensional Database
Architecture
Session
2B: Web Warehousing
14.00 – 15.30
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
Ji Zhang , Tok Wang Ling,
Robert M. Bruckner, A Min Tjoa (Singapore, Austria)
15.30 – 16.00 Coffee Break
Session
3: Change Detection
16.00 – 17.30
A Temporal Study of Data Sources to Load a Corporate Data Warehouse
Automatic Detection of Structural Changes in Data Warehouses
Johann Eder, Christian Koncilia, Dieter Mitsche (Austria)
Performance Tests in Data Warehousing ETLM Process for Detection of
Changes in Data Origin
Session
4: Web Mining and Association Rule
9.00 – 10.00
Mining Interesting Knowledge from Weblogs: A Survey
Parallel Vector Computing Technique for the Very Large Scale Web Graph
10.00 – 10.30 Coffee Break
Session
5: Association Rules and Decision
Trees
10.30 – 12.30
Ordinal Association Rules towards Association Rules
Sylvie
Guillaume (France)
Rough set-based Decision Tree model for Classification
Inference Based Classifier: Building Decision Trees Efficiently for
Categorical Attributes
Generating Effective Classifiers with Supervised Learning of Genetic
Programming
12.30 – 14.00 Lunch
14.00 – 15.30
Clustering by Regression Analysis
Handling large workloads by profiling and clustering
Incremental OPTICS: Efficient Computation of Updates in a Hierarchical
Cluster Ordering
15.30 – 16.00 Coffee Break
Session
7A: Clustering II
16.00 – 17.30
On Complementarity of Cluster and Oultier Detection Schemes
Cluster Validity Using Support Vector Machines
FSSM: Fast Construction of the Optimized Segment Support Map
16.00 – 17.30
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
Session
8: Data Analysis and Discovery
9.00 – 10.00
A Distance-based Approach to Find Interesting Patterns
Similarity Search in Structured Data
Hans-Peter
Kriegel, Stefan Schönauer (Germany)
10.00 – 10.30 Coffee Break
Session
9: Ontologies and Improving Data
Quality
10.30 – 12.00
Using Interest Ontology for Improved Support in Rule Mining
Integrate deceiving intention prediction with fraud detection
12.30 – 14.00 Lunch
Session
10A: Queries and Data Patterns
14.00 – 15.30
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
Session
10B: Improving Database Query
Engine
14.00 – 15.30
A New Computation Model for Rough Set Theory Based on Database Systems
Computing SQL subqueries with Boolean Aggregates
Fighting Redundancy in SQL: the For-loop approach
Antonio
Badia (USA.)
15.30 – 16.00 Coffee Break
Session
11: Sampling and Vector
Classification
16.00 – 17.00
“On-the-fly” vs. Materialized Sampling and Heuristics
Incremental and Decremental Proximal Support Vector Classification
using Decay Coefficients