Workshop Notes
Sixth International Workshop
“What can FCA do for Artificial Intelligence?”
FCA4AI 2018
International Joint Conference on Artificial Intelligence European Conference on Artificial Intelligence
IJCAI/ECAI 2018
July 13 2018 Stockholm, Sweden
Editors
Sergei O. Kuznetsov (NRU HSE Moscow) Amedeo Napoli (LORIA Nancy)
Sebastian Rudolph (TU Dresden)
http://fca4ai.hse.ru/2018/
Preface
The five preceding editions of the FCA4AI Workshop showed that many researchers work- ing in Artificial Intelligence are deeply interested by a well-founded method for classification and mining such as Formal Concept Analysis (seehttp://www.fca4ai.hse.ru/). The first edition of FCA4AI was co-located with ECAI 2012 in Montpellier, the second one with IJCAI 2013 in Beijing, the third one with ECAI 2014 in Prague, the fourth on with IJCAI 2015 in Buenos Aires, and finally the fifth one with ECAI 2016 in The Hague. All the proceedings of the preceding editions are published as CEUR Proceedings (http://ceur-ws.org/Vol-939/, http://ceur-ws.org/Vol-1058/,http://ceur-ws.org/Vol-1257/, andhttp://ceur-ws.
org/Vol-1430/, and http://ceur-ws.org/Vol-1703/).
This year, the workshop has again attracted many different researchers working on actual and important topics, e.g. theory, extensions of FCA (MDL), classification, mining of linked data, annotation, biclustering, recommendation and applications. This shows the diversity and the richness of the relations between FCA and AI.
Formal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classification. FCA allows one to build a concept lattice and a system of depen- dencies (implications) which can be used for many Artificial Intelligence needs, e.g. knowl- edge discovery, learning, knowledge representation, reasoning, ontology engineering, as well as information retrieval and text processing. As we can see, there are many “natural links”
between FCA and Artificial Intelligence. Recent years have been witnessing increased scien- tific activity around FCA, in particular a strand of work emerged that is aimed at extending the possibilities of FCA w.r.t. knowledge processing, such as work on pattern structures and relational context analysis. These extensions are aimed at allowing FCA to deal with more complex than just binary data, both from the data analysis and knowledge discovery points of view and as well from the knowledge representation point of view, including, e.g., ontol- ogy engineering. All these investigations provide new possibilities for Artificial Intelligence activities in the framework of FCA. Accordingly, in this workshop, we are interested in main issues such as:
• How can FCA support AI activities such as knowledge processing (knowledge discov- ery, knowledge representation and reasoning), learning (clustering, pattern and data mining), natural language processing, and information retrieval.
• How can FCA be extended in order to help Artificial Intelligence researchers to solve new and complex problems in their domains.
The workshop is dedicated to discuss such issues. This year, the papers submitted to the workshop were carefully peer-reviewed by three members of the program committee and 11 papers with the highest scores were selected. We thank all the PC members for their reviews and all the authors for their contributions.
The Workshop Chairs Sergei O. Kuznetsov
National Research University Higher School of Economics, Moscow, Russia Amedeo Napoli
LORIA (CNRS – Inria Nancy Grand Est – Université de Lorraine), Vandoeuvre les Nancy, France
Sebastian Rudolph
Technische Universität Dresden, Germany
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Program Committee
Mehwish Alam (STLab, CNR Bologna, Italy) Jaume Baixeries (UPC Barcelona, Catalunya)
Karell Bertet (Université de La Rochelle, France, Germany)
Aleksey Buzmakov (National Research University HSE Perm, Russia) Loïc Cerf (UFMG Belo-Horizonte, Brazil)
Victor Codocedo (UFTSM Santiago de Chile, Chile)
Mathieu D’Aquin (The National University of Ireland, Galway) Florent Domenach (Akita International University, Japan) Marianne Huchard (LIRMM/Université de Montpellier, France)
Dmitry I. Ignatov (National Research University HSE Moscow, Moscow, Russia) Mehdi Kaytoue (INSA-LIRIS Lyon, France)
Jan Konecny (Palacky University, Olomouc, Czech Republic) Florence Le Ber (ENGEES/Université de Strasbourg, France) Nizar Messai (Université de Tours, France)
Rokia Missaoui (Université du Québec en Outaouais, Ottawa, Canada) Sergei A. Obiedkov (NRU Higher School of Economics, Moscow, Russia) Jean-Marc Petit (INSA-LIRIS Lyon, France)
Uta Priss (Ostfalia University of Applied Sciences, Wolfenbüttel, Germany) Christian Săcărea (Babes-Bolyai University, Cluj-Napoca, Romania) Henry Soldano (Université de Paris-Nord, France)
Laszlo Szathmary, University of Debrecen, Hungary
Diana Troancă (Babes-Bolyai University, Cluj-Napoca, Romania) Renato Vimiero (UFPE Recife, Brazil)
Contents
1 Inductive Reasoning with Conceptual Space Representations (Invited Talk)
Zied Bouraoui . . . . 7 2 An Answer Set Programming environment for high-level specification and visualization
of FCA
Lucas Bourneuf . . . . 9 3 Three Approaches for Mining Definitions from Relational Data in the Web of Data
Justine Reynaud, Yannick Toussaint, and Amedeo Napoli . . . . 21 4 Relational proportions between objects and attributes
Nelly Barbot, Laurent Miclet, and Henri Prade . . . . 33 5 MDL for FCA: is there a place for background knowledge?
Tatiana Makhalova, Sergei O. Kuznetsov, and Amedeo Napoli . . . . 45 6 Rectangle and Square Coverings of Tolerance Spaces and their Direct Product
Christian Jäkel and Stefan E. Schmidt . . . . 57 7 The theory and practice of coupling formal concept analysis to relational databases
Jens Kötters and Peter W. Eklund . . . . 69 8 Generalized metrics with applications to ratings and formal concept analysis
Tobias Gäbel-Häkenschnieder, Thorsten Pfeiffer, and Stefan E. Schmidt . . . . 81 9 Binary Lattices
Célia Châtel, François Brucker, and Pascal Préa . . . . 93 10 Biclustering Based on FCA and Partition Pattern Structures for Recommendation
Systems
Nyoman Juniarta, Victor Codocedo, Miguel Couceiro, and Amedeo Napoli . . . 105 11 Combining Concept Annotation and Pattern Structures for Guiding Ontology Mapping
Pierre Monnin, Amedeo Napoli, and Adrien Coulet . . . 117 12 Understanding Collaborative Filtering with Galois Connections
Vladimir Kursitys and Dmitry Ignatov . . . 127
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