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Formal Concept Analysis

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Cover of 'Formal Concept Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Formal Concept Analysis
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    Chapter 2 Formal Concept Analysis from the Standpoint of Possibility Theory
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    Chapter 3 Measuring the Implications of the D -Basis in Analysis of Data in Biomedical Studies
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    Chapter 4 Formal Concept Analysis and Information Retrieval – A Survey
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    Chapter 5 Bonds Between $$L$$ -Fuzzy Contexts Over Different Structures of Truth-Degrees
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    Chapter 6 The Linear Algebra in Formal Concept Analysis over Idempotent Semifields
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    Chapter 7 On Closure Systems and Adjunctions Between Fuzzy Preordered Sets
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    Chapter 8 Extensional Confluences and Local Closure Operators
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    Chapter 9 A Note on Pattern Structures and Their Projections
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    Chapter 10 Exploring Pattern Structures of Syntactic Trees for Relation Extraction
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    Chapter 11 Totally Balanced Formal Context Representation
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    Chapter 12 Randomized Fuzzy Formal Contexts and Relevance of One-Sided Concepts
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    Chapter 13 Revisiting Pattern Structure Projections
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    Chapter 14 Exploring Faulty Data
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    Chapter 15 Automatic Validation of Terminology by Means of Formal Concept Analysis
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    Chapter 16 Towards a Navigation Paradigm for Triadic Concepts
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    Chapter 17 A Proposal for Extending Formal Concept Analysis to Knowledge Graphs
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    Chapter 18 Simple Undirected Graphs as Formal Contexts
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    Chapter 19 A Conceptual Approach for Relational IR: Application to Legal Collections
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Title
Formal Concept Analysis
Published by
Springer International Publishing, May 2015
DOI 10.1007/978-3-319-19545-2
ISBNs
978-3-31-919544-5, 978-3-31-919545-2
Editors

Baixeries, Jaume, Sacarea, Christian, Ojeda-Aciego, Manuel

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 33%
Unknown 2 67%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 67%
Other 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Mathematics 1 33%