CFP FCA4AI 2016 at ECAI 2016, The Hague, August 30 2016.

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-- FCA4AI (Fifth Edition) -- 
``What can FCA do for Artificial Intelligence?'' 
co-located with ECAI 2016, The Hague, Netherlands 
August 30 2016 
http://www.fca4ai.hse.ru/2016 


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General Information. 

The preceding editions of the FCA4AI Workshop (ECAI 2014 and 2012, IJCAI 2015 and 2013) showed that many researchers working in Artificial Intelligence are indeed interested by a powerful method for classification and mining such as Formal Concept Analysis (see CEUR Proceedings Vol-1430, Vol-1257, Vol-1058, and Vol-939). 
This year, we have the chance to organize a new edition of the workshop in The Hague at the ECAI 2016 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 involving learning, knowledge discovery, knowledge representation and reasoning, ontology engineering, and as well as information retrieval 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 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 point of view and from the knowledge representation point of view, including, e.g., ontology engineering. 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 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 domain. 

The workshop is dedicated to discuss 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. 

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: June 5, 2016 
Notification to authors: July 5, 2016 
Final version: July 25, 2016 
Workshop: August 30 


SUBMISSION DETAILS: 

The workshop welcomes submissions in pdf format in Springer's LNCS style. 
Submissions can be: 
- technical papers not exceeding 8 pages, 
- system descriptions or position papers on work in progress not 
exceeding 4 pages 

Submissions are via EasyChair at 
https://www.easychair.org/conferences/?conf=fca4ai2016 (to be opened soon) 

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 of 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 Technische Universitaet Dresden, Germany 

PROGRAM COMMITTEE (under construction) 

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