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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 Elements About Exploratory, Knowledge-Based, Hybrid, and Explainable Knowledge Discovery
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    Chapter 2 Too Much Information: Can AI Cope with Modern Knowledge Graphs?
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    Chapter 3 Learning Implications from Data and from Queries
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    Chapter 4 Concepts in Application Context
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    Chapter 5 Direct and Binary Direct Bases for One-Set Updates of a Closure System
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    Chapter 6 Reduction and Introducers in d -contexts
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    Chapter 7 Dualization in Lattices Given by Implicational Bases
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    Chapter 8 “ Properties of Finite Lattices ” by S. Reeg and W. Weiß, Revisited
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    Chapter 9 Joining Implications in Formal Contexts and Inductive Learning in a Horn Description Logic
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    Chapter 10 Lattices of Orders
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    Chapter 11 On-demand Relational Concept Analysis
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    Chapter 12 Mining Formal Concepts Using Implications Between Items
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    Chapter 13 Effects of Input Data Formalisation in Relational Concept Analysis for a Data Model with a Ternary Relation
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    Chapter 14 Parallelization of the GreConD Algorithm for Boolean Matrix Factorization
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    Chapter 15 Simultaneous, Polynomial-Time Layout of Context Bigraph and Lattice Digraph
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    Chapter 16 Using Redescriptions and Formal Concept Analysis for Mining Definitions in Linked Data
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    Chapter 17 A Formal Context for Closures of Acyclic Hypergraphs
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    Chapter 18 Concept Lattices as a Search Space for Graph Compression
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    Chapter 19 A Relational Extension of Galois Connections
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    Chapter 20 Sampling Representation Contexts with Attribute Exploration
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    Chapter 21 Discovering Implicational Knowledge in Wikidata
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    Chapter 22 A Characterization Theorem for Continuous Lattices by Closure Spaces
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    Chapter 23 On Coupling FCA and MDL in Pattern Mining
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    Chapter 24 A Study of Boolean Matrix Factorization Under Supervised Settings
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Title
Formal Concept Analysis
Published by
Springer International Publishing, July 2019
DOI 10.1007/978-3-030-21462-3
ISBNs
978-3-03-021461-6, 978-3-03-021462-3
Editors

Cristea, Diana, Le Ber, Florence, Sertkaya, Baris

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X Demographics

The data shown below were collected from the profiles of 19 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Other 1 50%
Student > Doctoral Student 1 50%
Readers by discipline Count As %
Computer Science 3 150%