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Data Warehousing and Knowledge Discovery

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Cover of 'Data Warehousing and Knowledge Discovery'

Table of Contents

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    Book Overview
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    Chapter 1 Conceptual Design of XML Document Warehouses
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    Chapter 2 Bringing Together Partitioning, Materialized Views and Indexes to Optimize Performance of Relational Data Warehouses
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    Chapter 3 GeoDWFrame: A Framework for Guiding the Design of Geographical Dimensional Schemas
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    Chapter 4 Workload-Based Placement and Join Processing in Node-Partitioned Data Warehouses
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    Chapter 5 Novelty Framework for Knowledge Discovery in Databases
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    Chapter 6 Revisiting Generic Bases of Association Rules
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    Chapter 7 Mining Maximal Frequently Changing Subtree Patterns from XML Documents
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    Chapter 8 Discovering Pattern-Based Dynamic Structures from Versions of Unordered XML Documents
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    Chapter 9 Space-Efficient Range-Sum Queries in OLAP
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    Chapter 10 Answering Approximate Range Aggregate Queries on OLAP Data Cubes with Probabilistic Guarantees
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    Chapter 11 Computing Complex Iceberg Cubes by Multiway Aggregation and Bounding
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    Chapter 12 An Aggregate-Aware Retargeting Algorithm for Multiple Fact Data Warehouses
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    Chapter 13 A Partial Pre-aggregation Scheme for HOLAP Engines
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    Chapter 14 Discovering Multidimensional Structure in Relational Data
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    Chapter 15 Inductive Databases as Ranking
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    Chapter 16 Inductive Databases of Polynomial Equations
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    Chapter 17 From Temporal Rules to Temporal Meta-rules
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    Chapter 18 How Is BI Used in Industry?: Report from a Knowledge Exchange Network
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    Chapter 19 Towards an Adaptive Approach for Mining Data Streams in Resource Constrained Environments
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    Chapter 20 Exploring Possible Adverse Drug Reactions by Clustering Event Sequences
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    Chapter 21 SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes
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    Chapter 22 Novel Clustering Approach that Employs Genetic Algorithm with New Representation Scheme and Multiple Objectives
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    Chapter 23 Categorical Data Visualization and Clustering Using Subjective Factors
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    Chapter 24 Multidimensional Data Visual Exploration by Interactive Information Segments
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    Chapter 25 Metadata to Support Transformations and Data & Metadata Lineage in a Warehousing Environment
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    Chapter 26 Classification Based on Attribute Dependency
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    Chapter 27 OWDEAH: Online Web Data Extraction Based on Access History
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    Chapter 28 Data Mining Approaches to Diffuse Large B–Cell Lymphoma Gene Expression Data Interpretation
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    Chapter 29 Deriving Multiple Topics to Label Small Document Regions
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    Chapter 30 Deriving Efficient SQL Sequences via Read-Aheads
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    Chapter 31 Diversity in Random Subspacing Ensembles
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    Chapter 32 Partitioned Approach to Association Rule Mining over Multiple Databases
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    Chapter 33 A Tree Partitioning Method for Memory Management in Association Rule Mining
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    Chapter 34 Mining Interesting Association Rules for Prediction in the Software Project Management Area
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    Chapter 35 PROWL: An Efficient Frequent Continuity Mining Algorithm on Event Sequences
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    Chapter 36 Algorithms for Discovery of Frequent Superset, Rather Than Frequent Subset
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    Chapter 37 Improving Direct Counting for Frequent Itemset Mining
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    Chapter 38 Mining Sequential Patterns with Item Constraints
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    Chapter 39 Mining Borders of the Difference of Two Datacubes
  41. Altmetric Badge
    Chapter 40 Mining Periodic Patterns in Sequence Data
Overall attention for this book and its chapters
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Title
Data Warehousing and Knowledge Discovery
Published by
Springer Berlin Heidelberg, November 2004
DOI 10.1007/b99817
ISBNs
978-3-54-022937-7, 978-3-54-030076-2
Editors

Kambayashi, Yahiko, Mohania, Mukesh, Wöß, Wolfram

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 14%
Unknown 12 86%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 50%
Student > Ph. D. Student 2 14%
Researcher 2 14%
Professor > Associate Professor 2 14%
Unknown 1 7%
Readers by discipline Count As %
Computer Science 11 79%
Arts and Humanities 1 7%
Earth and Planetary Sciences 1 7%
Unknown 1 7%