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Data Mining and Knowledge Discovery Handbook

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Cover of 'Data Mining and Knowledge Discovery Handbook'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction to Knowledge Discovery and Data Mining
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    Chapter 2 Data Cleansing: A Prelude to Knowledge Discovery
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    Chapter 3 Handling Missing Attribute Values
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    Chapter 4 Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour
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    Chapter 5 Dimension Reduction and Feature Selection
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    Chapter 6 Discretization Methods
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    Chapter 7 Outlier Detection
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    Chapter 8 Supervised Learning
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    Chapter 9 Classification Trees
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    Chapter 10 Bayesian Networks
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    Chapter 11 Data Mining within a Regression Framework
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    Chapter 12 Support Vector Machines
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    Chapter 13 Rule Induction
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    Chapter 14 A survey of Clustering Algorithms
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    Chapter 15 Association Rules
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    Chapter 16 Frequent Set Mining
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    Chapter 17 Constraint-based Data Mining
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    Chapter 18 Link Analysis
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    Chapter 19 A Review of Evolutionary Algorithms for Data Mining
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    Chapter 20 A Review of Reinforcement Learning Methods
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    Chapter 21 Neural Networks For Data Mining
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    Chapter 22 Granular Computing and Rough Sets - An Incremental Development
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    Chapter 23 Pattern Clustering Using a Swarm Intelligence Approach
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    Chapter 24 Using Fuzzy Logic in Data Mining
  26. Altmetric Badge
    Chapter 25 Statistical Methods for Data Mining
  27. Altmetric Badge
    Chapter 26 Logics for Data Mining
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    Chapter 27 Wavelet Methods in Data Mining
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    Chapter 28 Fractal Mining - Self Similarity-based Clustering and its Applications
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    Chapter 29 Visual Analysis of Sequences Using Fractal Geometry
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    Chapter 30 Interestingness Measures - On Determining What Is Interesting
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    Chapter 31 Quality Assessment Approaches in Data Mining
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    Chapter 32 Data Mining Model Comparison
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    Chapter 33 Data Mining Query Languages
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    Chapter 34 Mining Multi-label Data
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    Chapter 35 Privacy in Data Mining
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    Chapter 36 Meta-Learning - Concepts and Techniques
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    Chapter 37 Bias vs Variance Decomposition for Regression and Classification
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    Chapter 38 Mining with Rare Cases
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    Chapter 39 Data Stream Mining
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    Chapter 40 Mining Concept-Drifting Data Streams
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    Chapter 41 Mining High-Dimensional Data
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    Chapter 42 Text Mining and Information Extraction
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    Chapter 43 Spatial Data Mining
  45. Altmetric Badge
    Chapter 44 Data Mining and Knowledge Discovery Handbook
  46. Altmetric Badge
    Chapter 45 Data Mining for Imbalanced Datasets: An Overview
  47. Altmetric Badge
    Chapter 46 Relational Data Mining
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    Chapter 47 Web Mining
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    Chapter 48 A Review of Web Document Clustering Approaches
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    Chapter 49 Causal Discovery
  51. Altmetric Badge
    Chapter 50 Ensemble Methods in Supervised Learning
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    Chapter 51 Data Mining using Decomposition Methods
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    Chapter 52 Information Fusion - Methods and Aggregation Operators
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    Chapter 53 Parallel and Grid-Based Data Mining – Algorithms, Models and Systems for High-Performance KDD
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    Chapter 54 Collaborative Data Mining
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    Chapter 55 Organizational Data Mining
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    Chapter 56 Mining Time Series Data
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    Chapter 57 Multimedia Data Mining
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    Chapter 58 Data Mining in Medicine
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    Chapter 59 Learning Information Patterns in Biological Databases - Stochastic Data Mining
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    Chapter 60 Data Mining for Financial Applications
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    Chapter 61 Data Mining for Intrusion Detection
  63. Altmetric Badge
    Chapter 62 Data Mining for CRM
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    Chapter 63 Data Mining for Target Marketing
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    Chapter 64 NHECD - Nano Health and Environmental Commented Database
  66. Altmetric Badge
    Chapter 65 Commercial Data Mining Software
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    Chapter 66 Weka-A Machine Learning Workbench for Data Mining
Attention for Chapter 46: Relational Data Mining
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Chapter title
Relational Data Mining
Chapter number 46
Book title
Data Mining and Knowledge Discovery Handbook
Published in
ADS, January 2009
DOI 10.1007/978-0-387-09823-4_46
Book ISBNs
978-0-387-09822-7, 978-0-387-09823-4
Authors

Sašo Džeroski

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Italy 1 1%
Portugal 1 1%
Spain 1 1%
United Kingdom 1 1%
Unknown 74 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 21%
Researcher 13 16%
Student > Master 11 14%
Student > Bachelor 8 10%
Student > Doctoral Student 7 9%
Other 15 19%
Unknown 9 11%
Readers by discipline Count As %
Computer Science 56 70%
Engineering 3 4%
Business, Management and Accounting 2 3%
Social Sciences 2 3%
Chemistry 2 3%
Other 3 4%
Unknown 12 15%