Data Warehousing and Knowledge Discovery

Table of Contents

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   Book Overview
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   Chapter 1 UML-Based Modeling for What-If Analysis
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   Chapter 2 Model-Driven Metadata for OLAP Cubes from the Conceptual Modelling of Data Warehouses
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   Chapter 3 An MDA Approach for the Development of Spatial Data Warehouses
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   Chapter 4 Built-In Indicators to Discover Interesting Drill Paths in a Cube
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   Chapter 5 Upper Borders for Emerging Cubes
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   Chapter 6 Top_Keyword: An Aggregation Function for Textual Document OLAP
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   Chapter 7 Summarizing Distributed Data Streams for Storage in Data Warehouses
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   Chapter 8 Efficient Data Distribution for DWS
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    Chapter 9 Data Partitioning in Data Warehouses: Hardness Study, Heuristics and ORACLE Validation
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    Chapter 10 A Robust Sampling-Based Framework for Privacy Preserving OLAP
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    Chapter 11 Generalization-Based Privacy-Preserving Data Collection
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    Chapter 12 Processing Aggregate Queries on Spatial OLAP Data
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    Chapter 13 Efficient Incremental Maintenance of Derived Relations and BLAST Computations in Bioinformatics Data Warehouses
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    Chapter 14 Mining Conditional Cardinality Patterns for Data Warehouse Query Optimization
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    Chapter 15 Up and Down: Mining Multidimensional Sequential Patterns Using Hierarchies
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    Chapter 16 Efficient K- Means Clustering Using Accelerated Graphics Processors
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    Chapter 17 Extracting Knowledge from Life Courses: Clustering and Visualization
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    Chapter 18 A Hybrid Clustering Algorithm Based on Multi-swarm Constriction PSO and GRASP
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    Chapter 19 Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering
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    Chapter 20 Clustered Dynamic Conditional Correlation Multivariate GARCH Model
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    Chapter 21 Document Clustering by Semantic Smoothing and Dynamic Growing Cell Structure (DynGCS) for Biomedical Literature
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    Chapter 22 Mining Serial Episode Rules with Time Lags over Multiple Data Streams
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    Chapter 23 Efficient Approximate Mining of Frequent Patterns over Transactional Data Streams
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    Chapter 24 Continuous Trend-Based Clustering in Data Streams
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    Chapter 25 Mining Multidimensional Sequential Patterns over Data Streams
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    Chapter 26 Towards a Model Independent Method for Explaining Classification for Individual Instances
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    Chapter 27 Selective Pre-processing of Imbalanced Data for Improving Classification Performance
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    Chapter 28 A Parameter-Free Associative Classification Method
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    Chapter 29 The Evaluation of Sentence Similarity Measures
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    Chapter 30 Labeling Nodes of Automatically Generated Taxonomy for Multi-type Relational Datasets
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    Chapter 31 Towards the Automatic Construction of Conceptual Taxonomies
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    Chapter 32 Adapting LDA Model to Discover Author-Topic Relations for Email Analysis
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    Chapter 33 A New Semantic Representation for Short Texts
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    Chapter 34 Document-Base Extraction for Single-Label Text Classification
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    Chapter 35 How an Ensemble Method Can Compute a Comprehensible Model
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    Chapter 36 Empirical Analysis of Reliability Estimates for Individual Regression Predictions
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    Chapter 37 User Defined Partitioning - Group Data Based on Computation Model
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    Chapter 38 Workload-Aware Histograms for Remote Applications
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    Chapter 39 Is a Voting Approach Accurate for Opinion Mining?
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    Chapter 40 Mining Sequential Patterns with Negative Conclusions