-------------------------------------------------------------------------------------------------------------------
-- FCA4AI (Eighth
Edition) --
``What can FCA do for Artificial
Intelligence?''
co-located with ECAI 2020,
Santiago de Compostela, Spain
June 8 or 9 2020
http://www.fca4ai.hse.ru/2020
-------------------------------------------------------------------------------------------------------------------
General Information.
The preceding editions of the FCA4AI Workshop (from ECAI 2012
until IJCAI 2019) showed that many researchers working in
Artificial Intelligence are indeed interested by powerful
techniques for classification and data mining provided by
Formal Concept Analysis. Again, we have the chance to organize
a new edition of the workshop in Santiago de Compostela,
co-located with the ECAI 2020 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 and association rules) 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 are 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 plain FCA
w.r.t. knowledge processing, such as work on pattern
structures and relational context analysis, as well as on
hybridization with other formalisms. These extensions are
aimed at allowing FCA to deal with more complex than just
binary data, for solving complex problems in data analysis,
classification, knowledge processing... While the capabilities
of FCA are extended, new possibilities are arising in the
framework of FCA.
As usual, the FCA4AI workshop is dedicated to discuss such
issues, and in particular:
- How can FCA support AI activities in knowledge discovery,
knowledge representation and reasoning, machine learning,
natural language processing...
- By contrast, how the current developments in AI can be
integrated within FCA to help AI researchers to solve complex
problems in their domain.
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,
dimensionality reduction, classification, clustering, and
biclustering.
- Pattern mining, subgroup discovery, exceptional model
mining, interestingness measures, MDL-based approaches in data
mining.
- Machine learning and hybridization: neural networks, random
forests, SVM, and combination of classifiers with FCA.
- Knowledge engineering, knowledge representation and
reasoning, and ontology engineering.
- Scalable and distributed algorithms for FCA and artificial
intelligence, and for mining big data.
- AI tasks based on FCA: information retrieval,
recommendation, social network analysis, data visualization
and navigation, pattern recognition...
- Practical applications in agronomy, biology, chemistry,
finance, manufacturing, medicine...
The workshop will include time for audience discussion for
having a better understanding of the issues, challenges, and
ideas being presented.
IMPORTANT DATES:
Submission deadline: March 23 2020
Notification to authors: April 10 2020
Final version: April 30 2020
Workshop: June 8 or 9 2020
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=fca4ai2020
The workshop proceedings will be published as CEUR proceedings
(see preceding editions in CEUR Proceedings Vol-2529,
Vol-2149, Vol-1703, Vol-1430, Vol-1257, Vol-1058, and
Vol-939).
WORKSHOP CHAIRS:
Sergei O. Kuznetsov National Research University Higher
Schools of Economics, Moscow, Russia
Amedeo Napoli Université de Lorraine, CNRS, Inria,
LORIA, Nancy, France
Sebastian Rudolph Technische Universität Dresden, Germany
PROGRAM COMMITTEE (under construction)
-------------------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------------------