Vol-2729
urn:nbn:de:0074-2729-8

Copyright © 2020 for the individual papers by the papers' authors. Copyright © 2020 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

FCA4AI 2020
What can FCA do for Artificial Intelligence?

Proceedings of the 8th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2020)
co-located with 24th European Conference on Artificial Intelligence (ECAI 2020)

Santiago de Compostela, Spain, August 29, 2020.

Edited by

Sergei O. Kuznetsov *
Amedeo Napoli
Sebastian Rudolph *

* National Research University Higher School of Economics, Faculty of Computer Science, Moscow, Russia
** Université de Lorraine, CNRS, Inria, LORIA, F-54000, Nancy, France
*** Technische Universität, Dresden, Germany

Table of Contents

Preface

Embedding Formal Contexts Using Unordered Composition 7-18
Esteban Marquer, Ajinkya Kulkarni, Miguel Couceiro
Improving User's Experience in Navigating Concept Lattices: An Approach Based on Virtual Reality 19-30
Christian Sacarea, Raul-Robert Zavaczki
Dihypergraph Decomposition: Application to Closure System Representations 31-44
Simon Vilmin, Lhouari Nourine
Closure Structure: a Deeper Insight 45-56
Tatiana Makhalova, Sergei O. Kuznetsov, Amedeo Napoli
Towards Polynomial Subgroup Discovery by Means of FCA 57-68
Aleksey Buzmakov
Representation of Knowledge Using Different Structures of Concepts 69-74
Dmitry Palchunov, Gulnara Yakhyaeva
The Study of the Relationship Between Publications in Social Networks Communities via Formal Concept Analysis 75-80
Kristina Pakhomova, Alina Belova
Patterns via Clustering as a Data Mining Tool 81-90
Lars Lumpe, Stefan Schmidt
Interval-Based Sequence Mining Using FCA and the NextPriorityConcept Algorithm 91-102
Salah Eddine Boukhetta, Jérémy Richard, Christophe Demko, Karell Bertet
Continuous Attributes for FCA-based Machine Learning 103-112
Dmitry Vinogradov
Granular Computing and Incremental Classification 113-120
Xenia Naidenova, Vladimir Parkhomenko
Concept Lattice and Soft Sets. Application to the Medical Image Analysis 121-128
Anca Christine Pascu, Laurent Nana, Mayssa Tayachi
Estimation of Errors Rates for FCA-based Knowledge Discovery 129-140
Dmitry Vinogradov
Building a Representation Context Based on Attribute Exploration Algorithms 141-152
Jaume Baixeries, Victor Codocedo, Mehdi Kaytoue, Amedeo Napoli

2020-10-07: submitted by Sergei O. Kuznetsov, Amedeo Napoli, Sebastian Rudolph metadata incl. bibliographic data published under Creative Commons CC0
2020-11-06: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|