Data Warehousing and Knowledge Discovery

Table of Contents

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   Book Overview
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   Chapter 1 A Hilbert Space Compression Architecture for Data Warehouse Environments
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   Chapter 2 Evolution of Data Warehouses’ Optimization: A Workload Perspective
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   Chapter 3 What-If Analysis for Data Warehouse Evolution
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   Chapter 4 An Extensible Metadata Framework for Data Quality Assessment of Composite Structures
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   Chapter 5 Automating the Schema Matching Process for Heterogeneous Data Warehouses
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   Chapter 6 A Dynamic View Materialization Scheme for Sequences of Query and Update Statements
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   Chapter 7 Spatio-temporal Aggregations in Trajectory Data Warehouses
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   Chapter 8 Computing Join Aggregates over Private Tables
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    Chapter 9 An Annotation Management System for Multidimensional Databases
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    Chapter 10 On the Need of a Reference Algebra for OLAP
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    Chapter 11 Data Warehousing and Knowledge Discovery
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    Chapter 12 Built-In Indicators to Automatically Detect Interesting Cells in a Cube
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    Chapter 13 Emerging Cubes for Trends Analysis in Olap Databases
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    Chapter 14 Domination Mining and Querying
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    Chapter 15 Semantic Knowledge Integration to Support Inductive Query Optimization
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    Chapter 16 A Clustered Dwarf Structure to Speed Up Queries on Data Cubes
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    Chapter 17 An OLAM-Based Framework for Complex Knowledge Pattern Discovery in Distributed-and-Heterogeneous-Data-Sources and Cooperative Information Systems
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    Chapter 18 Integrating Clustering Data Mining into the Multidimensional Modeling of Data Warehouses with UML Profiles
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    Chapter 19 A UML Profile for Representing Business Object States in a Data Warehouse
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    Chapter 20 Selection and Pruning Algorithms for Bitmap Index Selection Problem Using Data Mining
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    Chapter 21 MOSAIC: A Proximity Graph Approach for Agglomerative Clustering
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    Chapter 22 A Hybrid Particle Swarm Optimization Algorithm for Clustering Analysis
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    Chapter 23 Clustering Transactions with an Unbalanced Hierarchical Product Structure
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    Chapter 24 Constrained Graph b-Coloring Based Clustering Approach
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    Chapter 25 An Efficient Algorithm for Identifying the Most Contributory Substring
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    Chapter 26 Mining High Utility Quantitative Association Rules
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    Chapter 27 Extraction of Association Rules Based on Literalsets
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    Chapter 28 Cost-Sensitive Decision Trees Applied to Medical Data
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    Chapter 29 Utilization of Global Ranking Information in Graph- Based Biomedical Literature Clustering
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    Chapter 30 Ontology-Based Information Extraction and Information Retrieval in Health Care Domain
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    Chapter 31 Fuzzy Classifier Based Feature Reduction for Better Gene Selection
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    Chapter 32 Two Way Focused Classification
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    Chapter 33 A Markov Blanket Based Strategy to Optimize the Induction of Bayesian Classifiers When Using Conditional Independence Learning Algorithms
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    Chapter 34 Learning of Semantic Sibling Group Hierarchies - K-Means vs. Bi-secting-K-Means
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    Chapter 35 Mining Top-K Multidimensional Gradients
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    Chapter 36 A Novel Similarity-Based Modularity Function for Graph Partitioning
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    Chapter 37 Dual Dimensionality Reduction for Efficient Video Similarity Search
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    Chapter 38 Privacy-Preserving Genetic Algorithms for Rule Discovery
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    Chapter 39 Fast Cryptographic Multi-party Protocols for Computing Boolean Scalar Products with Applications to Privacy-Preserving Association Rule Mining in Vertically Partitioned Data
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    Chapter 40 Privacy-Preserving Self-Organizing Map
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    Chapter 41 DWFIST: Leveraging Calendar-Based Pattern Mining in Data Streams
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    Chapter 42 Expectation Propagation in GenSpace Graphs for Summarization
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    Chapter 43 Mining First-Order Temporal Interval Patterns with Regular Expression Constraints
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    Chapter 44 Mining Trajectory Patterns Using Hidden Markov Models