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-- FCA4AI (Sixth
Edition) --
``What can FCA do for Artificial
Intelligence?''
co-located with IJCAI 2018,
Stockholm, Sweden
July 13 2018
http://www.fca4ai.hse.ru/2018
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General Information.
The five preceding editions of the FCA4AI Workshop (ECAI 2016,
2014 and 2012, IJCAI 2015 and 2013) showed that many
researchers working in Artificial Intelligence are indeed
interested in a powerful method for classification and mining
such as Formal Concept Analysis (see CEUR Proceedings
Vol-1703, Vol-1430, Vol-1257, Vol-1058, and Vol-939).
This year, we have the chance to organize a new edition of the
workshop in Stockholm co-located with the IJCAI 2018
Conference.
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 dependencies
(implications) which can be used for many AI needs, e.g.
knowledge processing, knowledge discovery, knowledge
representation and reasoning, ontology engineering, as well as
information retrieval, recommendation, social network analysis
and text processing. Thus, there exist many ``natural links''
between FCA and AI.
Recent years have been witnessing increased scientific
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 concept analysis. These extensions are aimed at
allowing FCA to deal with more complex than just binary data,
for solving problems in data analysis, knowledge discovery,
knowledge representation, ontology engineering, and many more.
All these works extend the capabilities of FCA and offer new
possibilities for AI activities in the framework of FCA.
Accordingly, in this workshop, we will be interested in the
following 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, or information retrieval?
- How can FCA be extended in order to help AI researchers to
solve new
and complex problems in their domain?
The workshop is dedicated to discussing such issues.
TOPICS OF INTEREST include but are not limited to:
- Concept lattices and related structures: description logics,
pattern structures, relational structures.
- Knowledge discovery and data mining with FCA: association
rules, itemsets and data dependencies, attribute implications,
data pre-processing, redundancy and dimensionality reduction,
classification and clustering.
- Knowledge engineering and ontology engineering: knowledge
representation and reasoning.
- Scalable algorithms for concept lattices and artificial
intelligence ``in the large'' (distributed aspects, big data).
- Applications of concept lattices: semantic web, information
retrieval, visualization and navigation, pattern recognition,
and practical applications in agronomy, biology, chemistry,
finance, manufacturing, medicine, etc.
The workshop will include time for audience discussion toward
developing a better understanding of the issues, challenges,
and ideas being presented.
IMPORTANT DATES:
Submission deadline: May 23 2018
Notification to authors: June 11 2018
Final version: June 25 2018
Workshop: July 13 2018
SUBMISSION DETAILS:
The workshop welcomes submissions in pdf format in Springer's
LNCS style.
Submissions can be:
- technical papers not exceeding 12 pages,
- system descriptions or position papers on work in progress
not
exceeding 6 pages.
Submissions are via EasyChair at
https://easychair.org/conferences/?conf=fca4ai2018
The workshop proceedings will be published as CEUR
proceedings.
A selection of the best papers presented at the workshop will
be considered for a special issue in a high-level journal.
WORKSHOP CHAIRS:
Sergei O. Kuznetsov Higher Schools of Economics, Moscow,
Russia
Amedeo Napoli LORIA-INRIA, Vandoeuvre les Nancy,
France
Sebastian Rudolph TU Dresden, Germany
PROGRAM COMMITTEE (under construction)
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