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Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications

Book Description

Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications provides a comprehensive analysis of current issues and trends in retrieval expansion. Containing research from leading international experts, this book presents future challenges and opportunities in the field valuable to academicians, researchers, and practitioners.

Table of Contents

  1. Copyright
  2. Editorial Advisory Board
  3. List of Reviewers
  4. Preface
  5. DWH Architectures and Fundamentals
    1. The LBF R-Tree: Scalable Indexing and Storage for Data Warehousing Systems
      1. ABSTRACT
      2. 1 INTRODUCTION
      3. 2 RELATED WORK
      4. 4 A NEW I/O EFFICIENT MODEL FOR DW ENVIRONMENTS
      5. 5 COMPRESSING THE LBF R-TREE
      6. 6 EXPERIMENTAL RESULTS
      7. 7 CONCLUSION
      8. 8 REFERENCES
    2. Dynamic Workload for Schema Evolution in Data Warehouses: A Performance Issue
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. GENERAL FRAMEWORK FOR SCHEMA EVOLUTION IN DATA WAREHOUSES
      5. WORKLOAD EVOLUTION: OUR APPROACH
      6. CASE STUDY
      7. IMPLEMENTATION ISSUES
      8. CONCLUSION
      9. ACKNOWLEDGMENT
      10. REFERENCES
      11. ENDNOTE
    3. Preview: Optimizing View Materialization Cost in Spatial Data Warehouses
      1. ABSTRACT
      2. 1 INTRODUCTION
      3. 2 SPATIAL QUERIES
      4. 3 THE UNIVERSAL COMPOSITE LATTICE
      5. 4 THE PREVIEW
      6. 5 THE EXTENDED COST MODEL OF A SPATIAL DATA WAREHOUSE
      7. 6 SPATIAL QUERY DECOMPOSITION AND EVALUATIONS
      8. 7 IMPLEMENTATIONS AND SIMULATION STUDY
      9. 8 RELATED WORKS
      10. 9 CONCLUSION
      11. REFERENCES
  6. Multidimensional Data and OLAP
    1. Decisional Annotations: Integrating and Preserving Decision-Makers' Expertise in Multidimensional Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. AN ANNOTATION-FEATURED MULTIDIMENSIONAL MODEL
      4. MULTIDIMENSIONAL CONCEPTS
      5. GRAPHICAL NOTATIONS
      6. MULTIDIMENSIONAL TABLE
      7. AN INTEGRATED ANNOTATION MODEL
      8. R-OLAP IMPLEMENTATION
      9. METABASE STRUCTURE
      10. SNOWFLAKE DATABASE
      11. ANNOTATION STORAGE
      12. AN ANNOTATED MULTIDIMENSIONAL DATABASE MANAGEMENT SYSTEM
      13. CONCLUDING REMARKS AND FUTURE WORKS
      14. REFERENCES
      15. ENDNOTES
    2. Federated Data Warehouses
      1. ABSTRACT
      2. INTRODUCTION
      3. APPROACHES AND CHOICES OF DW INTEGRATION
      4. MULTI-DIMENSIONAL CANONICAL DATA MODEL
      5. TAXONOMY OF CONFLICTS IN MULTI-DIMENSIONAL DATA
      6. FEDERATED DW REFERENCE ARCHITECTURE
      7. INTEGRATION METHODOLOGY OF DATA MARTS
      8. SQL-MDI—THE DISTRIBUTED OLAP LANGUAGE
      9. SUMMARY
      10. ACKNOWLEDGMENT
      11. REFERENCES
      12. ENDNOTES
    3. Built-In Indicators to Support Business Intelligence in OLAP Databases
      1. ABSTRACT
      2. INTRODUCTION
      3. DYNAMIC ANALYSIS
      4. STATIC ANALYSIS
      5. IMPLEMENTATION WITH ORACLE 10G
      6. CONCLUSION
      7. REFERENCES
      8. ENDNOTE
  7. DWH and OLAP Applications
    1. Conceptual Data Warehouse Design Methodology for Business Process Intelligence
      1. ABSTRACT
      2. INTRODUCTION
      3. BUSINESS PROCESS INTELLIGENCE
      4. CONTRIBUTION AND OUTLINE
      5. RELATED WORK
      6. MOTIVATING CASE STUDY
      7. REQUIREMENTS OF SURGICAL WORKFLOW ANALYSIS
      8. STRUCTURING SURGICAL WORKFLOWS
      9. CONTROL FLOWS VS. MULTIDIMENSIONAL CUBES
      10. BUSINESS PROCESS MODELING
      11. MULTIDIMENSIONAL DATA MODEL AND OLAP
      12. BUSINESS PROCESS DATA WAREHOUSE DESIGN: CHALLENGES
      13. STAGES OF THE CONCEPTUAL MODELING
      14. FUNDAMENTAL CONSTRAINTS OF THE MULTIDIMENSIONAL DATA MODEL
      15. CONCEPTUAL DATA WAREHOUSE DESIGN: TERMINOLOGY AND FORMALIZATION
      16. A UNIFIED MULTIDIMENSIONAL SPACE
      17. FACTS AND DIMENSIONS
      18. ADVANCED ELEMENTS OF THE CONCEPTUAL MODEL
      19. TYPES OF MULTI-FACT SCHEMES
      20. MODELING DIMENSION HIERARCHIES
      21. UNIFICATION OF THE MULTIDIMENSIONAL SPACE
      22. "FADING" DUALITY OF FACT AND DIMENSION ROLES
      23. OBTAINING A MULTIDIMENSIONAL SCHEME OF A PROCESS
      24. VERIFICATION AND REFINEMENT OF THE E/R SCHEME
      25. IDENTIFYING FACTS AND DIMENSIONS
      26. IDENTIFYING FACTS
      27. IDENTIFYING DIMENSIONS
      28. EVALUATION OF THE PROPOSED DESIGN
      29. IMPLEMENTATION REMARKS
      30. VISUAL ANALYSIS
      31. SAMPLE USAGE SCENARIOS
      32. CONCLUSION
      33. ACKNOWLEDGMENT
      34. REFERENCES
      35. APPENDIX A.
    2. Data Warehouse Facilitating Evidence—Based Medicine
      1. ABSTRACT
      2. INTRODUCTION
      3. EVIDENCE-BASED MEDICINE
      4. EXTERNAL SOURCES OF CLINICAL EVIDENCE
      5. CLINICAL DECISION SUPPORT SYSTEMS EMBRACING EVIDENCE-BASED GUIDELINES
      6. DEPLOYING DATA WAREHOUSES IN GENERATION OF EVIDENCE- BASED GUIDELINES
      7. CONTROLLING CLINICAL TREATMENT PATHWAYS WITH DATA WAREHOUSES INCORPORATING EBM
      8. EVIDENCE-BASED DECISION SUPPORT AT THE POINT OF CARE
      9. HEALTHCARE STANDARDS FOR MESSAGE EXCHANGE
      10. HL 7
      11. SEMANTIC INTEGRATION IN A FEDERATED DWH MODEL
      12. MEDICAL FEDERATED DWH INTEGRATION WORKFLOW
      13. MEDIATED QUERY SYSTEM IN AN HEALTHCARE ENVIRONMENT
      14. RUNNING EXAMPLE: FEDERATED DWH SUPPORTING CLINICIANS AT THE POINT OF CARE
      15. CONCLUSION
      16. REFERENCES
    3. Deploying Data Warehouses in Grids with Efficiency and Availability
      1. ABSTRACT
      2. INTRODUCTION
      3. FROM PARALLEL TO GRID- BASED DATA WAREHOUSES
      4. LOAD BALANCING AND HIGH AVAILABILITY IN GRID-NPDW
      5. EXPERIMENTAL RESULTS
      6. CONCLUSION
      7. REFERENCES
      8. ENDNOTES
  8. Data Mining Techniques
    1. MOSAIC: Agglomerative Clustering with Gabriel Graphs
      1. ABSTRACT
      2. 1 INTRODUCTION
      3. 2 POST-PROCESSING WITH MOSAIC
      4. 3 EXPERIMENTS
      5. 4 RELATED WORK
      6. 5 CONCLUSION
      7. 6 ACKNOWLEDGMENT
      8. REFERENCES
      9. ENDNOTES
    2. Ranking Gradients in Multi-Dimensional Spaces
      1. ABSTRACT
      2. 1 INTRODUCTION
      3. 2 RELATED WORK
      4. 3 GRADIENT QUERIES
      5. 4 PROBLEM FORMULATION
      6. 5 RAKING GRADIENTS IN MDS
      7. 6 PERFORMANCE STUDY
      8. 7 FINAL DISCUSSION
      9. REFERENCES
      10. ENDNOTE
    3. Simultaneous Feature Selection and Tuple Selection for Efficient Classification
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. RESULTS AND ANALYSIS
      5. CONCLUSION AND FUTURE DIRECTIONS
      6. REFERENCES
      7. ENDNOTES
  9. Advanced Mining Applications
    1. Learning Cost-Sensitive Decision Trees to Support Medical Diagnosis
      1. ABSTRACT
      2. INTRODUCTION
      3. TYPES OF COSTS
      4. CURRENT COST-SENSITIVE APPROACHES
      5. EVALUATION OF CLASSIFIERS
      6. A COST-SENSITIVE STRATEGY: TAKING RISK INTO ACCOUNT
      7. EXPERIMENTAL RESULTS
      8. CONCLUSION
      9. FUTURE TRENDS
      10. REFERENCES
      11. KEY TERMS AND DEFINITIONS
      12. ENDNOTE
      13. APPENDIX A. ARTIFICIAL DATA FOR CARDIAC DISEASE
    2. An Approximate Approach for Maintaining Recent Occurrences of Itemsets in a Sliding Window over Data Streams
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. PRELIMINARIES
      4. 3. PATTERNS MONITORING OVER A DATA STREAM OF TRANSACTION SEQUENCE
      5. 4. PATTERNS MONITORING OVER A GENERAL DATA STREAM
      6. 5. RECENTLY REPRESENTATIVE PATTERNS MINING
      7. 6. PERFORMANCE STUDY
      8. 7. CONCLUSION
      9. REFERENCES
    3. Protocol Identification of Encrypted Network Streams
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. APPROACH
      5. EXPERIMENTAL RESULTS
      6. DISCUSSION
      7. CONCLUSION
      8. REFERENCES
      9. ENDNOTE
    4. Exploring Calendar-Based Pattern Mining in Data Streams
      1. ABSTRACT
      2. INTRODUCTION
      3. CONTRIBUTIONS
      4. CONCLUSION
      5. REFERENCES
  10. Compilation of References
  11. About the Contributors
  12. Index