Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments | by David Taniar | 2010 | ISBN: 9781605667171. Parallel Multi-Dimensional ROLAP Indexing.
April 27th, 2010 | by kutenk |Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments
by David Taniar
2010 (448 pages)
ISBN:9781605667171
With contributions investigating theoretical queries along with real-world applications, this guide discusses developments in data mining and warehousing as well as techniques for successful implementation.
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Strategic Advancements in Utilizing Data Mining and Warehousing Technologies—New Concepts and Developments
Preface
INTRODUCTION
CURRENT TRENDS IN DATA WAREHOUSING
CURRENT TRENDS IN DATA MINING
CONCLUSION
REFERENCES
Chapter 1 – A Methodology Supporting the Design and Evaluating the Final Quality of Data Warehouses
ABSTRACT
INTRODUCTION AND MOTIVATION
RELATED WORK
PROPOSED INDEXES
DW-QUALITY METRIC
EXPERIMENTAL EVALUATION
ASSESSMENT
CONCLUSION
REFERENCES
Chapter 2 – Seismological Data Warehousing and Mining—A Survey
ABSTRACT
INTRODUCTION
THE ARCHITECTURE OF A SEISMIC DATA MANAGEMENT AND MINING SYSTEM
QUERYING, OLAP ANALYSIS, AND MINING
PROTOTYPE SYSTEMS AND TOOLS: A SURVEY
CONCLUSION
REFERENCES
Chapter 3 – Automated Integration of Heterogeneous Data Warehouse Schemas
ABSTRACT
INTRODUCTION
RELATED WORK
MATCHING STRATEGY FOR SOLVING HETEROGENEITIES AMONG MULTIDIMENSIONAL STRUCTURES
SIMILARITY FUNCTIONS FOR MULTIDIMENSIONAL STRUCTURES
MAPPING MULTIDIMENSIONAL STRUCTURES
EVALUATION OF ALGORITHM PERFORMANCE
CONCLUSION
REFERENCES
Chapter 4 – Algebraic and Graphic Languages for OLAP Manipulations
ABSTRACT
INTRODUCTION
CONCEPTUAL MODELING
MINIMAL CORE OF THE OLAP ALGEBRA
ADVANCED OPERATORS OF THE OLAP ALGEBRA
BINARY OPERATORS OF THE OLAP ALGEBRA
GRAPHICAL QUERY LANGUAGE
CONCLUDING REMARKS
REFERENCES
ENDNOTES
APPENDIX-A: CONSTELLATION GRAPHICAL VISUALIZATION
APPENDIX-B: COMPLEMENTARY FORMAL SPECIFICATIONS
Chapter 5 – Dynamic View Selection for OLAP
ABSTRACT
INTRODUCTION
PROBLEM DEFINITION AND RELATED WORK
RANDOMIZED ALGORITHMS FOR DYNAMIC VIEW SELECTION
GREEDY ALGORITHM FOR DYNAMIC VIEW SELECTION
EXPERIMENTAL RESULTS
CONCLUSION AND FUTURE WORK
REFERENCES
Chapter 6 – RCUBE—Parallel Multi-Dimensional ROLAP Indexing
ABSTRACT
INTRODUCTION
DISTRIBUTED INDEX CONSTRUCTION FOR ROLAP
DISTRIBUTED ROLAP QUERY ENGINE
PERFORMANCE ANALYSIS
CONCLUSION
ACKNOWLEDGMENT
REFERENCES
ENDNOTE
Chapter 7 – Medical Document Clustering Using Ontology-Based Term Similarity Measures
ABSTRACT
INTRODUCTION
TERM SEMANTIC SIMILARITY MEASURES
METHODOLOGY
DATASETS
EXPERIMENTAL RESULTS AND ANALYSIS
CONCLUSION AND FUTURE WORK
ACKNOWLEDGMENT
REFERENCES
Chapter 8 – A Graph-Based Biomedical Literature Clustering Approach Utilizing Term’s Global and Local Importance Information
ABSTRACT
INTRODUCTION
RELATED WORK
OUR METHOD
DATA SETS
TERM GLOBAL RANKING EVALUATION
TERM CLUSTERING EVALUATION
DOCUMENT CLUSTERING EVALUATION
CONCLUSION AND FUTURE WORK
ACKNOWLEDGMENT
REFERENCES
Chapter 9 – An Integrated Framework for Fuzzy Classification and Analysis of Gene Expression Data
ABSTRACT
INTRODUCTION
FEATURE SELECTION
RELATED WORK
CONSTRUCTING THE CORRELATION DATASET
MINING FREQUENT PATTERNS IN THE CORRELATION DATASET
EXPERIMENTAL RESULTS
CONCLUSION AND FUTURE WORK
REFERENCES
Chapter 10 – Vertical Fragmentation in Databases Using Data-Mining Technique
ABSTRACT
INTRODUCTION
RELATED WORK IN VERTICAL PARTITIONING
RELATED WORK IN ASSOCIATION RULES
METHODOLOGY
IMPLEMENTATION
EFFECTIVENESS OF PROPOSED METHOD
DISCUSSION
FUTURE RESEARCH
REFERENCES
APPENDIX A. TRANSACTIONS FOR TAE DATABASE
APPENDIX B: TRANSACTION SET FOR ADULTS DATABASE
Chapter 11 – Introducing the Elasticity of Spatial Data
ABSTRACT
INTRODUCTION
DETERMINING ELASTICITY OF IPRs
FORMATION OF ELASTICITY-BASED IPR GROUPINGS (EIGS)
INCORPORATING ELASTICITY INTO SPATIAL DATABASE MANAGEMENT PROCESSES
THE STUDY
DISCUSSION
CONCLUSION
REFERENCES
Chapter 12 – Sequential Patterns Postprocessing for Structural Relation Patterns Mining
ABSTRACT
INTRODUCTION
SEQUENTIAL PATTERNS MINING AND MODELLING
STRUCTURAL RELATION PATTERNS AND POSTSEQUENTIAL PATTERNS MINING
CONCURRENT PATTERNS MINING METHOD AND ALGORITHMS
EXPERIMENTS
CONCLUSION AND FUTURE WORK
ACKNOWLEDGMENT
REFERENCES
Chapter 13 – MILPRIT*—A Constraint-Based Algorithm for Mining Temporal Relational Patterns
ABSTRACT
INTRODUCTION AND MOTIVATION
PROBLEM FORMALIZATION
TEMPORAL PI-PATTERNS WITH RESTRICTIONS
THE ALGORITHM MILPRIT*
EXPERIMENTAL RESULTS
CONCLUSION AND FURTHER WORK
REFERENCES
ENDNOTES
APPENDIX: PROOF OF THEOREM 2 (OPTIMALITY)
Chapter 14 – Computing Join Aggregates over Private Tables
ABSTRACT
INTRODUCTION
RELATED WORK
PRELIMINARIES
METHOD
EXTENSIONS
EXPERIMENTS
DISCUSSIONS
REFERENCES
Chapter 15 – Overview of PAKDD Competition 2007
ABSTRACT
INTRODUCTION
PARTICIPATION AND RESULTS
DISCUSSION
BUSINESS INSIGHTS
CONCLUSION
ACKNOWLEDGMENT
REFERENCES
ENDNOTE
Chapter 16 – A Solution to the Cross-Selling Problem of PAKDD-2007—Ensemble Model of TreeNet and Logistic Regression
ABSTRACT
INTRODUCTION
SOFTWARE
DATA PREPROCESSING
MODELING
FINAL SCORES FOR PREDICTION DATASET
DISCUSSION
ACKNOWLEDGMENT
REFERENCES
Chapter 17 – Bagging Probit Models for Unbalanced Classification
ABSTRACT
INTRODUCTION
BAGGING WITH WEIGHTED RESAMPLING
DATA ANALYSIS AND MODEL SELECTION
APPLICATION AND TECHNICAL DISCUSSIONS
NOTES
REFERENCES
Chapter 18 – The Power of Sampling and Stacking for the PAKDD-2007 Cross-Selling Problem
ABSTRACT
INTRODUCTION
TECHNICAL APPROACH
EMBEDDING EXPERT’S KNOWLEDGE IN NEW VARIABLES
DATA PREPARATION
STRATIFIED SAMPLING STRATEGY
MODELING SYSTEM
PERFORMANCE EVALUATION AND METHODOLOGY
Kolmogorov-Smirnov Curve and its Maximum
EXPERIMENTAL RESULTS AND COMPARISONS
CONCLUDING REMARKS
REFERENCES
Chapter 19 – Using TreeNet to Cross-Sell Home Loans to Credit Card Holders
ABSTRACT
INTRODUCTION
THE MODELING CONTEXT
DATA OVERVIEW
MODELING
CONCLUSION
REFERENCES
Chapter 20 – PAKDD-2007—A Near-Linear Model for the Cross-Selling Problem
ABSTRACT
Applied Methodology
CONCLUSION
REFERENCES
Chapter 21 – Selecting Salient Features and Samples Simultaneously to Enhance Cross-Selling Model Performance
ABSTRACT
INTRODUCTION
PROBLEM DESCRIPTION
CRITERION OF FEATURE SELECTION
THE METHOD OF SAMPLE SELECTION
ALGORITHM COORDINATING FEATURE SELECTION AND SAMPLE SELECTION
EXPERIMENT
CONCLUSION
REFERENCES
Chapter 22 – Classification of Imbalanced Data with Random Sets and Mean-Variance Filtering
ABSTRACT
INTRODUCTION
MODELING TECHNIQUE
BOOSTING ALGORITHMS
AdaBoost ALGORITHM
EXPERIMENTAL RESULTS
CONCLUDING REMARKS AND FURTHER DEVELOPMENTS
REFERENCES
ENDNOTES
APPENDIX
Chapter 23 – Ranking Potential Customers Based on Group-Ensemble
ABSTRACT
INTRODUCTION
CONCLUSION AND FUTURE WORK
ACKNOWLEDGMENT
REFERENCES
Compilation of References
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