Vol-2528⫷ Vol-2529 ⫸Vol-2530
urn:nbn:de:0074-2529-2

Copyright © 2019 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 2019
What can FCA do for Artificial Intelligence?

Proceedings of the 7th International Workshop "What can FCA do for Artificial Intelligence"?
co-located with International Joint Conference on Artificial Intelligence ( IJCAI 2019 )

Macao, China, August 10, 2019 .

Edited by

Sergei O. Kuznetsov *
Amedeo Napoli
Sebastian Rudolph *

* NRU HSE , Faculty of Computer Science, Moscow, Russia
** Université de Lorraine, CNRS, Inria, LORIA , F-54000, Nancy, France
*** Technische Universität , Dresden, Germany

Table of Contents

Preface

Enabling Natural Language Analytics over Relational Data Using Formal Concept Analysis (short paper) 7-18
C. Anantaram , Mouli Rastogi , Mrinal Rawat , Pratik Saini
Using Formal Concept Analysis to Explain Black Box Deep Learning Classification Models (short paper) 19-26
Amit Sangroya , C. Anantaram , Mrinal Rawat , Mouli Rastogi
Validating Correctness of Textual Explanation with Complete Discourse Trees 29-38
Boris Galitsky , Dmitry Ilvovsky
Least General Generalization of the Linguistic Structures (short paper) 39-44
Boris Galitsky , Dmitry Ilvovsky
Truth and Justification in Knowledge Representation 45-56
Andrei Rodin , Serge Kovalyov
FCA-based Approach to Machine Learning (short paper) 57-64
Dmitry V. Vinogradov
Clustering of Biomedical Data Using the Greedy Clustering Algorithm Based on Interval Pattern Concepts (short paper) 65-74
Alexey V. Galatenko , Stepan A. Nersisyan , Vera V. Pankratieva
Increasing the Efficiency of Packet Classifiers with Closed Descriptions 75-86
Elizaveta F. Goncharova , Sergei O. Kuznetsov

2019-12-16: submitted by Amedeo Napoli, Tatiana Makhalova, metadata incl. bibliographic data published under Creative Commons CC0
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