Organizations rely on data mining and warehousing technologies to store, integrate, query, and analyze essential data.
Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments discusses developments in data mining and warehousing as well as techniques for successful implementation. Contributions investigate theoretical queries along with real-world applications, providing a useful foundation for academicians and practitioners to research new techniques and methodologies.
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Overview
Organizations rely on data mining and warehousing technologies to store, integrate, query, and analyze essential data.
Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments discusses developments in data mining and warehousing as well as techniques for successful implementation. Contributions investigate theoretical queries along with real-world applications, providing a useful foundation for academicians and practitioners to research new techniques and methodologies.
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Table of Contents
Ch. 1 A Methodology Supporting the Design and Evaluating the Final Quality of Data Warehouses 1
Ch. 2 Seismological Data Warehousing and Mining: A Survey 22
Ch. 3 Automated Integration of Heterogeneous Data Warehouse Schemas 38
Ch. 4 Algebraic and Graphic Languages for OLAP Manipulations 60
Ch. 5 Dynamic View Selection for OLAP 91
Ch. 6 RCUBE: Parallel Multi-Dimensional ROLAP Indexing 107
Ch. 7 Medical Document Clustering Using Ontology-Based Term Similarity Measures 121
Ch. 8 A Graph-Based Biomedical Literature Clustering Approach Utilizing Term's Global and Local Importance Information 133
Ch. 9 An Integrated Framework for Fuzzy Classification and Analysis of Gene expression Data 151
Ch. 10 Vertical Fragmentation in Databases Using Data-Mining Technique 178
Ch. 11 Introducing the Elasticity of Spatial Data 198
Ch. 12 Sequential Patterns Postprocessing for Structural Relation Patterns Mining 216
Ch. 13 MILPRIT*: A Constraint-Based Algorithm for Mining Temporal Relational Patterns 235
Ch. 14 Computing Join Aggregates Over Private Tables 256
Ch. 15 Overview of PAKDD Competition 2007 277
Ch. 16 A Solution to the Cross-Selling Problem of PAKDD-2007: Ensemble Model of TreeNet and Logistic Regression 285
Ch. 17 Bagging Probit Models for Unbalanced Classification 290
Ch. 18 The Power of Sampling and Stacking for the PaKDD-2007 Cross-Selling Problem 297
Ch. 19 Using TreeNet to Cross-Sell Home Loans to Credit Card Holders 307
Ch. 20 PAKDD-2007: A Near-Linear Model for the Cross-Selling Problem 320
Ch. 21 Selecting Salient Features and Samples Simultaneously to Enhance Cross-Selling Model Performance 329
Ch. 22 Classification ofImbalanced Data with Random sets and Mean-Variance Filtering 338
Ch. 23 Ranking Potential Customers Based on Group-Ensemble 355
Compilation of References 366
Index 402