Strategic Advancements In Utilizing Data Mining And Warehousing Technologies

Strategic Advancements In Utilizing Data Mining And Warehousing Technologies

by David Taniar
     
 

ISBN-10: 160566717X

ISBN-13: 9781605667171

Pub. Date: 09/01/2010

Publisher: IGI Global

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

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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.

Product Details

ISBN-13:
9781605667171
Publisher:
IGI Global
Publication date:
09/01/2010
Pages:
450
Product dimensions:
8.50(w) x 11.00(h) x 1.00(d)

Related Subjects

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

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