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Data Warehousing and Knowledge Discovery: 6th International Conference, DaWaK 2004, Zaragoza, Spain, September 1-3, 2004, Proceedings de Yahiko Kambayashi

Data Warehousing and Knowledge Discovery: 6th International Conference, DaWaK 2004, Zaragoza, Spain, September 1-3, 2004, Proceedings: Lecture Notes in Computer Science, cartea 3181

Editat de Yahiko Kambayashi, Mukesh Mohania, Wolfram Wöß
en Limba Engleză Paperback – 18 aug 2004
This book constitutes the refereed proceedings of the 5th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2003, held in Prague, Czech Republic in September 2003.
The 41 revised full papers presented were carefully reviewed and selected from more than 130 submissions. The papers are organized in topical sections on data cubes and queries, multidimensional data models, Web warehousing, change detection, Web mining and association rules, association rules and decision trees, clustering, association rule mining, data analysis and discovery, ontologies and improving data quality, queries and data patterns, improving database query engines, and sampling and vector classification.
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Specificații

ISBN-13: 9783540229377
ISBN-10: 354022937X
Pagini: 432
Ilustrații: XIV, 412 p.
Dimensiuni: 155 x 235 x 23 mm
Greutate: 1 kg
Ediția:2004
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Lecture Notes in Computer Science

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

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.

Caracteristici

Includes supplementary material: sn.pub/extras