Data Warehousing and Knowledge Discovery: 7th International Conference, DaWak 2005, Copenhagen, Denmark, August 22-26, 2005, Proceedings by A Min TjoaData Warehousing and Knowledge Discovery: 7th International Conference, DaWak 2005, Copenhagen, Denmark, August 22-26, 2005, Proceedings by A Min Tjoa

Data Warehousing and Knowledge Discovery: 7th International Conference, DaWak 2005, Copenhagen…

byA Min Tjoa

Paperback | August 17, 2005

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For more than a decade, data warehousing and knowledge discovery technologies have been developing into key technologies for decision-making processes in com- nies. Since 1999, due to the relevant role of these technologies in academia and ind- try, the Data Warehousing and Knowledge Discovery (DaWaK) conference series have become an international forum where both practitioners and researchers share their findings, publish their relevant results and dispute in depth research issues and experiences on data warehousing and knowledge discovery systems and applications. The 7th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2005) continued series of successful conferences dedicated to these topics. In this edition, the conference tried to provide the right, logical balance between data warehousing and knowledge discovery. Regarding data warehousing, papers cover different relevant and still unsolved research problems, such as the modelling of ETL processes and integration problems, designing OLAP technologies from XML do- ments, modelling data warehouses and data mining applications together, impro- ments in query processing, partitioning and implementations. With regard to data mining, a variety of papers were presented on subjects including data mining te- niques, clustering, classification, text documents and classification, and patterns. These proceedings contain the technical papers that were selected for presentation at the conference. We received 196 abstracts, and finally received 162 papers from 38 countries, and the Program Committee eventually selected 51 papers, making an acceptance rate of 31.4 % of submitted papers.
Title:Data Warehousing and Knowledge Discovery: 7th International Conference, DaWak 2005, Copenhagen…Format:PaperbackDimensions:544 pagesPublished:August 17, 2005Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:354028558X

ISBN - 13:9783540285588

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Table of Contents

Data Warehouse I.- A Tree Comparison Approach to Detect Changes in Data Warehouse Structures.- Extending the UML for Designing Association Rule Mining Models for Data Warehouses.- Event-Feeded Dimension Solution.- XML-OLAP: A Multidimensional Analysis Framework for XML Warehouses.- Data Warehouse II.- Graph-Based Modeling of ETL Activities with Multi-level Transformations and Updates.- Extending UML 2 Activity Diagrams with Business Intelligence Objects.- Automatic Selection of Bitmap Join Indexes in Data Warehouses.- Evaluating Data Warehouses and Tools.- A Survey of Open Source Tools for Business Intelligence.- DWEB: A Data Warehouse Engineering Benchmark.- A Set of Quality Indicators and Their Corresponding Metrics for Conceptual Models of Data Warehouses.- Design and Development of a Tool for Integrating Heterogeneous Data Warehouses.- Schema Transformations.- An Evolutionary Approach to Schema Partitioning Selection in a Data Warehouse.- Using Schema Transformation Pathways for Incremental View Maintenance.- Data Mapper: An Operator for Expressing One-to-Many Data Transformations.- Materialized Views.- Parallel Consistency Maintenance of Materialized Views Using Referential Integrity Constraints in Data Warehouses.- Selective View Materialization in a Spatial Data Warehouse.- PMC: Select Materialized Cells in Data Cubes.- Aggregates.- Progressive Ranking of Range Aggregates.- On Efficient Storing and Processing of Long Aggregate Lists.- Data Warehouse Queries and Database Processing Issues.- Ad Hoc Star Join Query Processing in Cluster Architectures.- A Precise Blocking Method for Record Linkage.- Flexible Query Answering in Data Cubes.- An Extendible Array Based Implementation of Relational Tables for Multi Dimensional Databases.- Data Mining Algorithms and Techniques.- Nearest Neighbor Search on Vertically Partitioned High-Dimensional Data.- A Machine Learning Approach to Identifying Database Sessions Using Unlabeled Data.- Hybrid System of Case-Based Reasoning and Neural Network for Symbolic Features.- Data Mining.- Spatio-temporal Rule Mining: Issues and Techniques.- Hybrid Approach to Web Content Outlier Mining Without Query Vector.- Incremental Data Mining Using Concurrent Online Refresh of Materialized Data Mining Views.- A Decremental Algorithm for Maintaining Frequent Itemsets in Dynamic Databases.- Association Rules.- Discovering Richer Temporal Association Rules from Interval-Based Data.- Semantic Query Expansion Combining Association Rules with Ontologies and Information Retrieval Techniques.- Maintenance of Generalized Association Rules Under Transaction Update and Taxonomy Evolution.- Prince: An Algorithm for Generating Rule Bases Without Closure Computations.- Text Processing and Classification.- Efficient Compression of Text Attributes of Data Warehouse Dimensions.- Effectiveness of Document Representation for Classification.- 2-PS Based Associative Text Classification.- Miscellaneous Applications.- Intrusion Detection via Analysis and Modelling of User Commands.- Dynamic Schema Navigation Using Formal Concept Analysis.- Security and Privacy Issues.- FMC: An Approach for Privacy Preserving OLAP.- Information Driven Evaluation of Data Hiding Algorithms.- Patterns.- Essential Patterns: A Perfect Cover of Frequent Patterns.- Processing Sequential Patterns in Relational Databases.- Optimizing a Sequence of Frequent Pattern Queries.- A General Effective Framework for Monotony and Tough Constraint Based Sequential Pattern Mining.- Cluster and Classification I.- Hiding Classification Rules for Data Sharing with Privacy Preservation.- Clustering-Based Histograms for Multi-dimensional Data.- Weighted K-Means for Density-Biased Clustering.- Cluster and Classification II.- A New Approach for Cluster Detection for Large Datasets with High Dimensionality.- Gene Expression Biclustering Using Random Walk Strategies.- Spectral Kernels for Classification.- Data Warehousing and Knowledge Discovery: A Chronological View of Research Challenges.