Data Warehousing and Knowledge Discovery

Conceptual Design and Modeling.- UML-Based Modeling for What-If Analysis.- Model-Driven Metadata for OLAP Cubes from the Conceptual Modelling of Data Warehouses.- An MDA Approach for the Development of Spatial Data Warehouses.- OLAP and Cube Processing.- Built-In Indicators to Discover Interesting Drill Paths in a Cube.- Upper Borders for Emerging Cubes.- Top_Keyword: An Aggregation Function for Textual Document OLAP.- Distributed Data Warehouse.- Summarizing Distributed Data Streams for Storage in Data Warehouses.- Efficient Data Distribution for DWS.- Data Partitioning in Data Warehouses: Hardness Study, Heuristics and ORACLE Validation.- Data Privacy in Data Warehouse.- A Robust Sampling-Based Framework for Privacy Preserving OLAP.- Generalization-Based Privacy-Preserving Data Collection.- Processing Aggregate Queries on Spatial OLAP Data.- Data Warehouse and Data Mining.- Efficient Incremental Maintenance of Derived Relations and BLAST Computations in Bioinformatics Data Warehouses.- Mining Conditional Cardinality Patterns for Data Warehouse Query Optimization.- Up and Down: Mining Multidimensional Sequential Patterns Using Hierarchies.- Clustering I.- Efficient K-Means Clustering Using Accelerated Graphics Processors.- Extracting Knowledge from Life Courses: Clustering and Visualization.- A Hybrid Clustering Algorithm Based on Multi-swarm Constriction PSO and GRASP.- Clustering II.- Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering.- Clustered Dynamic Conditional Correlation Multivariate GARCH Model.- Document Clustering by Semantic Smoothing and Dynamic Growing Cell Structure (DynGCS) for Biomedical Literature.- Mining Data Streams.- Mining Serial Episode Rules with Time Lags over Multiple Data Streams.- Efficient Approximate Mining of Frequent Patterns over Transactional Data Streams.- Continuous Trend-Based Clustering in Data Streams.- Mining Multidimensional Sequential Patterns over Data Streams.- Classification.- Towards a Model