International Workshop \What can FCA do for Arti cial Intelligence?" International Joint Conference on Arti cial Intelligence FCA4AI
IJCAI 2013
This is the second edition of the FCA4AI workshop, the rst edition being associated to the ECAI 2012 Conference, held in Montpellier, in August 2012 (see http://www.fca4ai. hse.ru/). In particular, the rst edition of the workshop showed that there are many AI researchers interested in FCA. Based on that, the three co-editors decided to organize a second edition of the FCA4AI workshop at the IJCAI 2013 Conference in Beijing.
Formal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classi cation. FCA allows one to build a concept lattice and a system of dependencies (implications) which can be used for many AI needs, e.g. knowledge processing involving learning, knowledge discovery, knowledge representation and reasoning, ontology engineering, as well as information retrieval and text processing. Thus, there exist many \natural links" between FCA and AI.
Recent years have been witnessing increased scienti c 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 from the knowledge representation point of view, including, e.g., ontology engineering.
All these works extend the capabilities of FCA and o er new possibilities for AI activities in the framework of FCA. Accordingly, in this workshop, we are interested in two main issues: How can FCA support AI activities such as knowledge processing (knowledge discovery, knowledge representation and reasoning), learning (clustering, pattern and data mining), natural language processing, information retrieval.
How can FCA be extended in order to help AI researchers to solve new and complex problems in their domains.
The workshop is dedicated to discuss such issues. The papers submitted to the workshop were carefully peer-reviewed by two 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. We also thank the organizing committee of ECAI-2012 and especially workshop chairs Jer^ome Lang and Michele Sebag for the support of the workshop.
Sergei O. Kuznetsov National Research University Higher Schools of Economics, Moscow, Russia Amedeo Napoli LORIA (CNRS { INRIA { Universite de Lorraine), Vandoeuvre les Nancy, France Sebastian Rudolph Technische Universitat Dresden, Germany Program Committee
Franz Baader (Technische Universitat Dresden, Germany) Karell Bertet (Universite de La Rochelle, France, Germany) Claudio Carpineto (Fondazione Ugo Bordoni, Roma, Italy) Felix Distel (Technische Universitat Dresden, Germany) Peter Eklund (University of Wollongong, Australia) Sebastien Ferre (IRISA Rennes, France) Pascal Hitzler (Wright State University, Dayton, Ohio, USA) Dmitry I. Ignatov (NRU Higher School of Economics, Moscow, Russia) Mehdi Kaytoue (INSA - LIRIS Lyon, France) Markus Krotzsch (University of Oxford, UK) Sergei A. Obiedkov (NRU Higher School of Economics, Moscow, Russia) Uta Priss (Ostfalia University of Applied Sciences, Wolfenbuttel, Germany) Baris Sertkaya (SAP Dresden, Germany) Henry Soldano (Universite de Paris-Nord, France)
Aleksey Buzmakov, Elias Egho, Nicolas Jay, Sergei O. Kuznetsov, Amedeo Napoli and Chedy Rassi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
V ctor Codocedo, Ioanna Lykourentzou, Hernan Astudillo and Amedeo Napoli 15
Jamel Eddine Jridi and Guy Lapalme . . . . . . . . . . . . . . . . . . . . . . 25
Pablo Cordero, Manuel Enciso, Angel Mora Bonilla and Manuel Ojeda-Aciego 33
Artem Revenko . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Aleksey Buzmakov and Alexey Neznanov . . . . . . . . . . . . . . . . . . . . 49