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Knowledge Discovery in Databases: PKDD 2003

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Cover of 'Knowledge Discovery in Databases: PKDD 2003'

Table of Contents

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    Book Overview
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    Chapter 1 From Knowledge-Based to Skill-Based Systems: Sailing as a Machine Learning Challenge
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    Chapter 2 Two-Eyed Algorithms and Problems
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    Chapter 3 Next Generation Data Mining Tools: Power Laws and Self-similarity for Graphs, Streams and Traditional Data
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    Chapter 4 Taking Causality Seriously: Propensity Score Methodology Applied to Estimate the Effects of Marketing Interventions
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    Chapter 5 Efficient Statistical Pruning of Association Rules
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    Chapter 6 Majority Classification by Means of Association Rules
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    Chapter 7 Adaptive Constraint Pushing in Frequent Pattern Mining
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    Chapter 8 ExAnte: Anticipated Data Reduction in Constrained Pattern Mining
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    Chapter 9 Minimal k -Free Representations of Frequent Sets
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    Chapter 10 Discovering Unbounded Episodes in Sequential Data
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    Chapter 11 Mr-SBC: A Multi-relational Naïve Bayes Classifier
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    Chapter 12 SMOTEBoost: Improving Prediction of the Minority Class in Boosting
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    Chapter 13 Using Belief Networks and Fisher Kernels for Structured Document Classification
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    Chapter 14 A Skeleton-Based Approach to Learning Bayesian Networks from Data
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    Chapter 15 On Decision Boundaries of Naïve Bayes in Continuous Domains
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    Chapter 16 Knowledge Discovery in Databases: PKDD 2003
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    Chapter 17 Visualizing Class Probability Estimators
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    Chapter 18 Automated Detection of Epidemics from the Usage Logs of a Physicians’ Reference Database
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    Chapter 19 An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations
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    Chapter 20 Preference Mining: A Novel Approach on Mining User Preferences for Personalized Applications
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    Chapter 21 Explaining Text Clustering Results Using Semantic Structures
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    Chapter 22 Analyzing Attribute Dependencies
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    Chapter 23 Ranking Interesting Subspaces for Clustering High Dimensional Data
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    Chapter 24 Efficiently Finding Arbitrarily Scaled Patterns in Massive Time Series Databases
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    Chapter 25 Using Transduction and Multi-view Learning to Answer Emails
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    Chapter 26 Exploring Fringe Settings of SVMs for Classification
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    Chapter 27 Rule Discovery and Probabilistic Modeling for Onomastic Data
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    Chapter 28 Constraint-Based Mining of Sequential Patterns over Datasets with Consecutive Repetitions
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    Chapter 29 Symbolic Distance Measurements Based on Characteristic Subspaces
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    Chapter 30 The Pattern Ordering Problem
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    Chapter 31 Collaborative Filtering Using Restoration Operators
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    Chapter 32 Efficient Frequent Query Discovery in Farmer
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    Chapter 33 Towards Behaviometric Security Systems: Learning to Identify a Typist
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    Chapter 34 Efficient Density Clustering Method for Spatial Data
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    Chapter 35 Statistical σ -Partition Clustering over Data Streams
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    Chapter 36 Enriching Relational Learning with Fuzzy Predicates
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    Chapter 37 Text Categorisation Using Document Profiling
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    Chapter 38 A Simple Algorithm for Topic Identification in 0–1 Data
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    Chapter 39 Bottom-Up Learning of Logic Programs for Information Extraction from Hypertext Documents
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    Chapter 40 Predicting Outliers
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    Chapter 41 Mining Rules of Multi-level Diagnostic Procedure from Databases
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    Chapter 42 Learning Characteristic Rules Relying on Quantified Paths
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    Chapter 43 Topic Learning from Few Examples
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    Chapter 44 Arbogodaï, a New Approach for Decision Trees
Overall attention for this book and its chapters
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Citations

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Title
Knowledge Discovery in Databases: PKDD 2003
Published by
Springer, Berlin, Heidelberg, January 2003
DOI 10.1007/b13634
ISBNs
978-3-54-020085-7, 978-3-54-039804-2
Editors

Nada Lavrač, Dragan Gamberger, Ljupčo Todorovski, Hendrik Blockeel

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Belgium 1 <1%
United Kingdom 1 <1%
France 1 <1%
Denmark 1 <1%
China 1 <1%
Greece 1 <1%
Portugal 1 <1%
Unknown 100 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 32%
Student > Master 29 27%
Student > Doctoral Student 10 9%
Researcher 9 8%
Student > Bachelor 4 4%
Other 17 16%
Unknown 5 5%
Readers by discipline Count As %
Computer Science 59 54%
Engineering 16 15%
Business, Management and Accounting 8 7%
Social Sciences 7 6%
Agricultural and Biological Sciences 5 5%
Other 9 8%
Unknown 5 5%