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Advances in Knowledge Discovery and Management

Overview of attention for book
Cover of 'Advances in Knowledge Discovery and Management'

Table of Contents

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    Book Overview
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    Chapter 1 Online Learning of a Weighted Selective Naive Bayes Classifier with Non-convex Optimization
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    Chapter 2 On Making Skyline Queries Resistant to Outliers
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    Chapter 3 Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures
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    Chapter 4 Exact and Approximate Minimal Pattern Mining
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    Chapter 5 Comparison of Proximity Measures for a Topological Discrimination
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    Chapter 6 Comparison of Linear Modularization Criteria Using the Relational Formalism, an Approach to Easily Identify Resolution Limit
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    Chapter 7 A Novel Approach to Feature Selection Based on Quality Estimation Metrics
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    Chapter 8 Ultrametricity of Dissimilarity Spaces and Its Significance for Data Mining
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    Chapter 9 SMERA: Semantic Mixed Approach for Web Query Expansion and Reformulation
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    Chapter 10 Multi-layer Ontologies for Integrated 3D Shape Segmentation and Annotation
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    Chapter 11 Ontology Alignment Using Web Linked Ontologies as Background Knowledge
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    Chapter 12 LIAISON: reconciLIAtion of Individuals Profiles Across SOcial Networks
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    Chapter 13 Clustering of Links and Clustering of Nodes: Fusion of Knowledge in Social Networks
Attention for Chapter 6: Comparison of Linear Modularization Criteria Using the Relational Formalism, an Approach to Easily Identify Resolution Limit
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mendeley
8 Mendeley
Summary
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Chapter title
Comparison of Linear Modularization Criteria Using the Relational Formalism, an Approach to Easily Identify Resolution Limit
Chapter number 6
Book title
Advances in Knowledge Discovery and Management
Published by
Springer International Publishing, November 2016
DOI 10.1007/978-3-319-45763-5_6
Book ISBNs
978-3-31-945762-8, 978-3-31-945763-5
Authors

Patricia Conde-Céspedes, Jean-François Marcotorchino, Emmanuel Viennet

Editors

Fabrice Guillet, Bruno Pinaud, Gilles Venturini

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Student > Bachelor 1 13%
Student > Master 1 13%
Professor > Associate Professor 1 13%
Student > Postgraduate 1 13%
Other 0 0%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 2 25%
Economics, Econometrics and Finance 2 25%
Chemical Engineering 1 13%
Engineering 1 13%
Unknown 2 25%

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