Beyond Databases, Architectures, and Structures

10th International Conference, BDAS 2014, Ustron, Poland, May 27-30, 2014. Proceedings

ISBN: 978-3-319-06931-9 (Print) 978-3-319-06932-6 (Online)

Table of contents (56 chapters)

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  1. Front Matter

    Pages 1-14

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    Pages 1-9

    Using the Model of Continuous Dynamical System with Viscous Resistance Forces for Improving Distribution Prediction Based on Evolution of Quantiles

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    Pages 10-19

    The exIWO Metaheuristic – A Recapitulation of the Research on the Join Ordering Problem

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    Pages 20-29

    Colored Petri Net Model of X/Open Distributed Transaction Processing Environment with Single Application Program

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    Pages 30-39

    Granular Indices for HQL Analytic Queries

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    Pages 40-49

    Performance Analysis of .NET Based Object–Relational Mapping Frameworks

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    Pages 50-60

    Standardization of NoSQL Database Languages

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    Pages 61-71

    Research on the Stream ETL Process

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    Pages 72-81

    XML Warehouse Modelling and Querying

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    Pages 82-91

    Unifying Mobility Data Warehouse Models Using UML Profile

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    Pages 92-101

    Data Quality Issues Concerning Statistical Data Gathering Supported by Big Data Technology

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    Pages 102-111

    Reasoning with Projection in Multimodular Description Logics Knowledge Bases

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    Pages 112-123

    Contextualizing a Knowledge Base by Approximation - A Case Study

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    Pages 124-138

    SMAQ – A Semantic Model for Analytical Queries

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    Pages 139-147

    An Ontology-Enabled Approach for Modelling Business Processes

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    Pages 148-159

    Rule-Based Algorithm Transforming OWL Ontology Into Relational Database

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    Pages 160-169

    Grouping Multiple RDF Graphs in the Collections

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    Pages 170-179

    Optimization of Approximate Decision Rules Relative to Coverage

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    Pages 180-190

    Nondeterministic Decision Rules in Rule-Based Classifier

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    Pages 191-200

    Extraction of Rules Dependencies for Optimization of Backward Inference Algorithm

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    Book Chapter

    Pages 201-210

    The Incompleteness Factor Method as a Support of Inference in Decision Support Systems

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