Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications | by Tho Manh Nguyen (ed) | 2010 | ISBN: 9781605667485. Computer Reference Guide. IT Reference Guide. Data Warehouse Architectures. Data Warehouse Design Methodology.
Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications
by Tho Manh Nguyen (ed)
2010 (426 pages)
ISBN:9781605667485
Presenting future challenges and opportunities in the field, this book provides a comprehensive analysis on current issues and trends in retrieval expansion.
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Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development—Innovative Methods and Applications
Preface
Section 1 – DWH Architectures and Fundamentals
Chapter 1 – The LBF R-Tree—Scalable Indexing and Storage for Data Warehousing Systems
ABSTRACT
1: INTRODUCTION
2: RELATED WORK
4: A NEW I/O EFFICIENT MODEL FOR DW ENVIRONMENTS
5: COMPRESSING THE LBF R-TREE
6: EXPERIMENTAL RESULTS
7: CONCLUSION
8: REFERENCES
Chapter 2 – Dynamic Workload for Schema Evolution in Data Warehouses—A Performance Issue
ABSTRACT
INTRODUCTION
RELATED WORK
GENERAL FRAMEWORK FOR SCHEMA EVOLUTION IN DATA WAREHOUSES
WORKLOAD EVOLUTION: OUR APPROACH
CASE STUDY
IMPLEMENTATION ISSUES
CONCLUSION
ACKNOWLEDGMENT
REFERENCES
ENDNOTE
Chapter 3 – Preview—Optimizing View Materialization Cost in Spatial Data Warehouses
ABSTRACT
1: INTRODUCTION
2: SPATIAL QUERIES
3: THE UNIVERSAL COMPOSITE LATTICE
4: THE PREVIEW
5: THE EXTENDED COST MODEL OF A SPATIAL DATA WAREHOUSE
6: SPATIAL QUERY DECOMPOSITION AND EVALUATIONS
7: IMPLEMENTATIONS AND SIMULATION STUDY
8: RELATED WORKS
9: CONCLUSION
REFERENCES
Section 2 – Multidimensional Data and OLAP
Chapter 4 – Decisional Annotations—Integrating and Preserving Decision-Makers’ Expertise in Multidimensional Systems
ABSTRACT
INTRODUCTION
AN ANNOTATION-FEATURED MULTIDIMENSIONAL MODEL
MULTIDIMENSIONAL CONCEPTS
GRAPHICAL NOTATIONS
MULTIDIMENSIONAL TABLE
AN INTEGRATED ANNOTATION MODEL
R-OLAP IMPLEMENTATION
METABASE STRUCTURE
SNOWFLAKE DATABASE
ANNOTATION STORAGE
AN ANNOTATED MULTIDIMENSIONAL DATABASE MANAGEMENT SYSTEM
CONCLUDING REMARKS AND FUTURE WORKS
REFERENCES
ENDNOTES
Chapter 5 – Federated Data Warehouses
ABSTRACT
INTRODUCTION
APPROACHES AND CHOICES OF DW INTEGRATION
MULTI-DIMENSIONAL CANONICAL DATA MODEL
TAXONOMY OF CONFLICTS IN MULTI-DIMENSIONAL DATA
FEDERATED DW REFERENCE ARCHITECTURE
INTEGRATION METHODOLOGY OF DATA MARTS
SQL-MDI—THE DISTRIBUTED OLAP LANGUAGE
SUMMARY
ACKNOWLEDGMENT
REFERENCES
ENDNOTES
Chapter 6 – Built—In Indicators to Support Business Intelligence in OLAP Databases
ABSTRACT
INTRODUCTION
DYNAMIC ANALYSIS
STATIC ANALYSIS
IMPLEMENTATION WITH ORACLE 10G
CONCLUSION
REFERENCES
ENDNOTE
Section 3 – DWH and OLAP Applications
Chapter 7 – Conceptual Data Warehouse Design Methodology for Business Process Intelligence
ABSTRACT
INTRODUCTION
BUSINESS PROCESS INTELLIGENCE
CONTRIBUTION AND OUTLINE
RELATED WORK
MOTIVATING CASE STUDY
REQUIREMENTS OF SURGICAL WORKFLOW ANALYSIS
STRUCTURING SURGICAL WORKFLOWS
CONTROL FLOWS VS. MULTIDIMENSIONAL CUBES
BUSINESS PROCESS MODELING
MULTIDIMENSIONAL DATA MODEL AND OLAP
BUSINESS PROCESS DATA WAREHOUSE DESIGN: CHALLENGES
STAGES OF THE CONCEPTUAL MODELING
FUNDAMENTAL CONSTRAINTS OF THE MULTIDIMENSIONAL DATA MODEL
CONCEPTUAL DATA WAREHOUSE DESIGN: TERMINOLOGY AND FORMALIZATION
A UNIFIED MULTIDIMENSIONAL SPACE
FACTS AND DIMENSIONS
ADVANCED ELEMENTS OF THE CONCEPTUAL MODEL
TYPES OF MULTI-FACT SCHEMES
MODELING DIMENSION HIERARCHIES
UNIFICATION OF THE MULTIDIMENSIONAL SPACE
“FADING” DUALITY OF FACT AND DIMENSION ROLES
OBTAINING A MULTIDIMENSIONAL SCHEME OF A PROCESS
VERIFICATION AND REFINEMENT OF THE E/R SCHEME
IDENTIFYING FACTS AND DIMENSIONS
IDENTIFYING FACTS
IDENTIFYING DIMENSIONS
EVALUATION OF THE PROPOSED DESIGN
IMPLEMENTATION REMARKS
VISUAL ANALYSIS
SAMPLE USAGE SCENARIOS
CONCLUSION
ACKNOWLEDGMENT
REFERENCES
APPENDIX A.
Chapter 8 – Data Warehouse Facilitating Evidence-Based Medicine
ABSTRACT
INTRODUCTION
EVIDENCE-BASED MEDICINE
EXTERNAL SOURCES OF CLINICAL EVIDENCE
CLINICAL DECISION SUPPORT SYSTEMS EMBRACING EVIDENCE-BASED GUIDELINES
DEPLOYING DATA WAREHOUSES IN GENERATION OF EVIDENCE-BASED GUIDELINES
CONTROLLING CLINICAL TREATMENT PATHWAYS WITH DATA WAREHOUSES INCORPORATING EBM
EVIDENCE-BASED DECISION SUPPORT AT THE POINT OF CARE
HEALTHCARE STANDARDS FOR MESSAGE EXCHANGE
SEMANTIC INTEGRATION IN A FEDERATED DWH MODEL
MEDICAL FEDERATED DWH INTEGRATION WORKFLOW
MEDIATED QUERY SYSTEM IN AN HEALTHCARE ENVIRONMENT
RUNNING EXAMPLE: FEDERATED DWH SUPPORTING CLINICIANS AT THE POINT OF CARE
CONCLUSION
REFERENCES
Chapter 9 – Deploying Data Warehouses in Grids with Efficiency and Availability
ABSTRACT
INTRODUCTION
FROM PARALLEL TO GRID-BASED DATA WAREHOUSES
LOAD BALANCING AND HIGH AVAILABILITY IN GRID-NPDW
EXPERIMENTAL RESULTS
CONCLUSION
REFERENCES
ENDNOTES
Section 4 – Data Mining Techniques
Chapter 10 – MOSAIC—Agglomerative Clustering with Gabriel Graphs
ABSTRACT
1: INTRODUCTION
2: POST-PROCESSING WITH MOSAIC
3: EXPERIMENTS
4: RELATED WORK
5: CONCLUSION
6: ACKNOWLEDGMENT
REFERENCES
ENDNOTES
Chapter 11 – Ranking Gradients in Multi-Dimensional Spaces
ABSTRACT
1: INTRODUCTION
2: RELATED WORK
3: GRADIENT QUERIES
4: PROBLEM FORMULATION
5: RAKING GRADIENTS IN MDS
6: PERFORMANCE STUDY
7: FINAL DISCUSSION
REFERENCES
ENDNOTE
Chapter 12 – Simultaneous Feature Selection and Tuple Selection for Efficient Classification
ABSTRACT
INTRODUCTION
RELATED WORK
RESULTS AND ANALYSIS
CONCLUSION AND FUTURE DIRECTIONS
REFERENCES
ENDNOTES
Section 5 – Advanced Mining Applications
Chapter 13 – Learning Cost—Sensitive Decision Trees to Support Medical Diagnosis
ABSTRACT
INTRODUCTION
TYPES OF COSTS
CURRENT COST-SENSITIVE APPROACHES
EVALUATION OF CLASSIFIERS
A COST-SENSITIVE STRATEGY: TAKING RISK INTO ACCOUNT
EXPERIMENTAL RESULTS
CONCLUSION
FUTURE TRENDS
REFERENCES
KEY TERMS AND DEFINITIONS
ENDNOTE
APPENDIX A. ARTIFICIAL DATA FOR CARDIAC DISEASE
Chapter 14 – An Approximate Approach for Maintaining Recent Occurrences of Itemsets in a Sliding Window over Data Streams
ABSTRACT
1: INTRODUCTION
2: PRELIMINARIES
3: PATTERNS MONITORING OVER A DATA STREAM OF TRANSACTION SEQUENCE
4: PATTERNS MONITORING OVER A GENERAL DATA STREAM
5: RECENTLY REPRESENTATIVE PATTERNS MINING
6: PERFORMANCE STUDY
7: CONCLUSION
REFERENCES
Chapter 15 – Protocol Identification of Encrypted Network Streams
ABSTRACT
INTRODUCTION
BACKGROUND
APPROACH
EXPERIMENTAL RESULTS
DISCUSSION
CONCLUSION
REFERENCES
ENDNOTE
Chapter 16 – Exploring Calendar—Based Pattern Mining in Data Streams
ABSTRACT
INTRODUCTION
CONTRIBUTIONS
CONCLUSION
REFERENCES
Compilation of References
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