Logic List Mailing Archive

FCA4AI 2020: What can FCA do for AI?

8-9 Jun 2020
Santiago de Compostela, Spain

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-- 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

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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)

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