Database Theory and Application : International Conference, DTA 2009, Held as Part of the Future Generation Information Technology Conference, FGIT 2009, Jeju Island, Korea, December 10-12, 2009, Proceedings

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ISBN 10: 3642105823 / ISBN 13: 9783642105821

Edité par Springer-Verlag GmbH, 2009

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Zustand: Sehr gut | Seiten: 186 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 6132094/12

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Titre : Database Theory and Application : ...

Éditeur : Springer-Verlag GmbH

Date d'édition : 2009

Reliure : Couverture souple

Etat : Sehr gut

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Synopsis :

Steganalysis for Reversible Data Hiding.- An Incremental View Maintenance Approach Using Version Store in Warehousing Environment.- The Study of Synchronization Framework among Multi-datasets.- Clustering News Articles in NewsPage.com Using NTSO.- Categorizing News Articles Using NTC without Decomposition.- A Comparative Analysis of XML Schema Languages.- Mining Approximate Frequent Itemsets over Data Streams Using Window Sliding Techniques.- Preserving Referential Integrity Constraints in XML Data Transformation.- Know-Ont: Engineering a Knowledge Ontology for an Enterprise.- Transformation of Data with Constraints for Integration: An Information System Approach.- Comparative Analysis of XLMiner and Weka for Association Rule Mining and Clustering.- Infobright for Analyzing Social Sciences Data.- Enhanced Statistics for Element-Centered XML Summaries.- Algorithm for Enumerating All Maximal Frequent Tree Patterns among Words in Tree-Structured Documents and Its Application.- A Method for Learning Bayesian Networks by Using Immune Binary Particle Swarm Optimization.- A Semantics-Preserving Approach for Extracting OWL Ontologies from UML Class Diagrams.- Data Warehousing and Business Intelligence: Benchmark Project for the Platform Selection.- Automatic Extraction of Decision Rules from Non-deterministic Data Systems: Theoretical Foundations and SQL-Based Implementation.- Soft Set Approach for Maximal Association Rules Mining.- Soft Set Theoretic Approach for Dimensionality Reduction.- Rough Set Approach for Categorical Data Clustering.