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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
Attention for Chapter 36: Enriching Relational Learning with Fuzzy Predicates
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Chapter title
Enriching Relational Learning with Fuzzy Predicates
Chapter number 36
Book title
Knowledge Discovery in Databases: PKDD 2003
Published by
Springer, Berlin, Heidelberg, September 2003
DOI 10.1007/978-3-540-39804-2_36
Book ISBNs
978-3-54-020085-7, 978-3-54-039804-2
Authors

Henri Prade, Gilles Richard, Mathieu Serrurier

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 25%
Unknown 3 75%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Student > Bachelor 1 25%
Other 1 25%
Readers by discipline Count As %
Computer Science 4 100%