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Autorenporträt
Yahiko Kambayashi, University of Kyoto, Japan / Mukesh Mohania, I.B.M. India Research Lab., New Delhi, India / Wolfgang Wöß, University of Linz, Austria
Inhaltsangabe
Data Warehousing Design.- Conceptual Design of XML Document Warehouses.- Bringing Together Partitioning, Materialized Views and Indexes to Optimize Performance of Relational Data Warehouses.- GeoDWFrame: A Framework for Guiding the Design of Geographical Dimensional Schemas.- Workload-Based Placement and Join Processing in Node-Partitioned Data Warehouses.- Knowledge Discovery Framework and XML Data Minig.- Novelty Framework for Knowledge Discovery in Databases.- Revisiting Generic Bases of Association Rules.- Mining Maximal Frequently Changing Subtree Patterns from XML Documents.- Discovering Pattern-Based Dynamic Structures from Versions of Unordered XML Documents.- Data Cubes and Queries.- Space-Efficient Range-Sum Queries in OLAP.- Answering Approximate Range Aggregate Queries on OLAP Data Cubes with Probabilistic Guarantees.- Computing Complex Iceberg Cubes by Multiway Aggregation and Bounding.- Multidimensional Schema and Data Aggregation.- An Aggregate-Aware Retargeting Algorithm for Multiple Fact Data Warehouses.- A Partial Pre-aggregation Scheme for HOLAP Engines.- Discovering Multidimensional Structure in Relational Data.- Inductive Databases and Temporal Rules.- Inductive Databases as Ranking.- Inductive Databases of Polynomial Equations.- From Temporal Rules to Temporal Meta-rules.- Industrial Track.- How Is BI Used in Industry?: Report from a Knowledge Exchange Network.- Towards an Adaptive Approach for Mining Data Streams in Resource Constrained Environments.- Data Clustering.- Exploring Possible Adverse Drug Reactions by Clustering Event Sequences.- SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes.- Novel Clustering Approach that Employs Genetic Algorithm with New Representation Scheme and Multiple Objectives.- Data Visualizationand Exploration.- Categorical Data Visualization and Clustering Using Subjective Factors.- Multidimensional Data Visual Exploration by Interactive Information Segments.- Metadata to Support Transformations and Data & Metadata Lineage in a Warehousing Environment.- Data Classification, Extraction and Interpretation.- Classification Based on Attribute Dependency.- OWDEAH: Online Web Data Extraction Based on Access History.- Data Mining Approaches to Diffuse Large B-Cell Lymphoma Gene Expression Data Interpretation.- Data Semantics.- Deriving Multiple Topics to Label Small Document Regions.- Deriving Efficient SQL Sequences via Read-Aheads.- Diversity in Random Subspacing Ensembles.- Association Rule Mining.- Partitioned Approach to Association Rule Mining over Multiple Databases.- A Tree Partitioning Method for Memory Management in Association Rule Mining.- Mining Interesting Association Rules for Prediction in the Software Project Management Area.- Mining Event Sequences.- PROWL: An Efficient Frequent Continuity Mining Algorithm on Event Sequences.- Algorithms for Discovery of Frequent Superset, Rather Than Frequent Subset.- Pattern Mining.- Improving Direct Counting for Frequent Itemset Mining.- Mining Sequential Patterns with Item Constraints.- Mining Borders of the Difference of Two Datacubes.- Mining Periodic Patterns in Sequence Data.
Data Warehousing Design.- Conceptual Design of XML Document Warehouses.- Bringing Together Partitioning, Materialized Views and Indexes to Optimize Performance of Relational Data Warehouses.- GeoDWFrame: A Framework for Guiding the Design of Geographical Dimensional Schemas.- Workload-Based Placement and Join Processing in Node-Partitioned Data Warehouses.- Knowledge Discovery Framework and XML Data Minig.- Novelty Framework for Knowledge Discovery in Databases.- Revisiting Generic Bases of Association Rules.- Mining Maximal Frequently Changing Subtree Patterns from XML Documents.- Discovering Pattern-Based Dynamic Structures from Versions of Unordered XML Documents.- Data Cubes and Queries.- Space-Efficient Range-Sum Queries in OLAP.- Answering Approximate Range Aggregate Queries on OLAP Data Cubes with Probabilistic Guarantees.- Computing Complex Iceberg Cubes by Multiway Aggregation and Bounding.- Multidimensional Schema and Data Aggregation.- An Aggregate-Aware Retargeting Algorithm for Multiple Fact Data Warehouses.- A Partial Pre-aggregation Scheme for HOLAP Engines.- Discovering Multidimensional Structure in Relational Data.- Inductive Databases and Temporal Rules.- Inductive Databases as Ranking.- Inductive Databases of Polynomial Equations.- From Temporal Rules to Temporal Meta-rules.- Industrial Track.- How Is BI Used in Industry?: Report from a Knowledge Exchange Network.- Towards an Adaptive Approach for Mining Data Streams in Resource Constrained Environments.- Data Clustering.- Exploring Possible Adverse Drug Reactions by Clustering Event Sequences.- SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes.- Novel Clustering Approach that Employs Genetic Algorithm with New Representation Scheme and Multiple Objectives.- Data Visualizationand Exploration.- Categorical Data Visualization and Clustering Using Subjective Factors.- Multidimensional Data Visual Exploration by Interactive Information Segments.- Metadata to Support Transformations and Data & Metadata Lineage in a Warehousing Environment.- Data Classification, Extraction and Interpretation.- Classification Based on Attribute Dependency.- OWDEAH: Online Web Data Extraction Based on Access History.- Data Mining Approaches to Diffuse Large B-Cell Lymphoma Gene Expression Data Interpretation.- Data Semantics.- Deriving Multiple Topics to Label Small Document Regions.- Deriving Efficient SQL Sequences via Read-Aheads.- Diversity in Random Subspacing Ensembles.- Association Rule Mining.- Partitioned Approach to Association Rule Mining over Multiple Databases.- A Tree Partitioning Method for Memory Management in Association Rule Mining.- Mining Interesting Association Rules for Prediction in the Software Project Management Area.- Mining Event Sequences.- PROWL: An Efficient Frequent Continuity Mining Algorithm on Event Sequences.- Algorithms for Discovery of Frequent Superset, Rather Than Frequent Subset.- Pattern Mining.- Improving Direct Counting for Frequent Itemset Mining.- Mining Sequential Patterns with Item Constraints.- Mining Borders of the Difference of Two Datacubes.- Mining Periodic Patterns in Sequence Data.
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