Formal Concept Analysis

15th International Conference, ICFCA 2019, Frankfurt, Germany, June 25–28, 2019, Proceedings

Häftad, Engelska, 2019

Av Diana Cristea, Florence Le Ber, Baris Sertkaya

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This book constitutes the proceedings of the 15th International Conference on Formal Concept Analysis, ICFCA 2019, held in Frankfurt am Main, Germany, in June 2019.The 15 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 36 submissions.

Produktinformation

Utgivningsdatum2019-05-23
Mått155 x 235 x 20 mm
Vikt552 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor349
FörlagSpringer Nature Switzerland AG
ISBN9783030214616

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Invited papers.- Elements about Hybrid, Exploratory, and Explainable Knowledge Discovery.- Too Much Information: Can AI Cope With Modern Knowledge Graphs.- Learning Implications from Data and from Queries.- Concepts in Application Context.- Theory.- Direct and Binary Direct Bases for One-set Updates of a Closure System.- Dualization in lattices given by implicational bases.- Properties of Finite Lattices.- Joining Implications in Formal Contexts and Inductive Learning in a Horn Description Logic.- Methods and Applications .- On-demand Relational Concept Analysis.- Mining Formal Concepts using Implications between Items.- Effects of Input Data Formalisation in Relational Concept Analysis for a Data Model with a Ternary Relation.- Parallelization of the GreConD Algorithm for Boolean Matrix Factorization.- Simultaneous, polynomial-time layout of Context Bigraph and Lattice Digraph.- Using Redescriptions and Formal Concept Analysis for Mining Definitions in Linked Data.- Enhanced FCA.- A Formal Context for Closures of Acyclic Hypergraphs.- Concept lattices as a search space for graph compression.- A relational extension of Galois Connections.- Short Papers.- Sampling Representation Contexts with Attribute Exploration.- Discovering Implicational Knowledge in Wikidata.- A characterization theorem for continuous lattices by closure spaces.- On Coupling FCA and MDL in Pattern Mining.- A Study of Boolean Matrix Factorization Under Supervised Settings.