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Data Warehousing and Knowledge Discovery

Overview of attention for book
Cover of 'Data Warehousing and Knowledge Discovery'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    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
  15. Altmetric Badge
    Chapter 14 Mining Conditional Cardinality Patterns for Data Warehouse Query Optimization
  16. Altmetric Badge
    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
  18. Altmetric Badge
    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
  21. Altmetric Badge
    Chapter 20 Clustered Dynamic Conditional Correlation Multivariate GARCH Model
  22. Altmetric Badge
    Chapter 21 Document Clustering by Semantic Smoothing and Dynamic Growing Cell Structure (DynGCS) for Biomedical Literature
  23. Altmetric Badge
    Chapter 22 Mining Serial Episode Rules with Time Lags over Multiple Data Streams
  24. Altmetric Badge
    Chapter 23 Efficient Approximate Mining of Frequent Patterns over Transactional Data Streams
  25. Altmetric Badge
    Chapter 24 Continuous Trend-Based Clustering in Data Streams
  26. Altmetric Badge
    Chapter 25 Mining Multidimensional Sequential Patterns over Data Streams
  27. Altmetric Badge
    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
  33. Altmetric Badge
    Chapter 32 Adapting LDA Model to Discover Author-Topic Relations for Email Analysis
  34. Altmetric Badge
    Chapter 33 A New Semantic Representation for Short Texts
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    Chapter 34 Document-Base Extraction for Single-Label Text Classification
  36. Altmetric Badge
    Chapter 35 How an Ensemble Method Can Compute a Comprehensible Model
  37. Altmetric Badge
    Chapter 36 Empirical Analysis of Reliability Estimates for Individual Regression Predictions
  38. Altmetric Badge
    Chapter 37 User Defined Partitioning - Group Data Based on Computation Model
  39. Altmetric Badge
    Chapter 38 Workload-Aware Histograms for Remote Applications
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    Chapter 39 Is a Voting Approach Accurate for Opinion Mining?
  41. Altmetric Badge
    Chapter 40 Mining Sequential Patterns with Negative Conclusions
Overall attention for this book and its chapters
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Mentioned by

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1 patent

Readers on

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235 Mendeley
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Title
Data Warehousing and Knowledge Discovery
Published by
ADS, August 2008
DOI 10.1007/978-3-540-85836-2
ISBNs
978-3-54-085835-5, 978-3-54-085836-2
Editors

Song, Il-Yeol, Eder, Johann, Nguyen, Tho Manh

Timeline

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 235 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 235 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 <1%
Unknown 234 100%
Readers by discipline Count As %
Computer Science 1 <1%
Unknown 234 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 July 2022.
All research outputs
#7,485,894
of 22,880,230 outputs
Outputs from ADS
#9,301
of 37,396 outputs
Outputs of similar age
#29,946
of 83,014 outputs
Outputs of similar age from ADS
#54
of 205 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 37,396 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 83,014 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 205 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.