(Updated) 29 - 30 August 2020, 8th Workshop "What can FCA do for AI?" (FCA4AI 2020), Santiago de Compostela, Spain
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. 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. While the capabilities of FCA are extended, new possibilities are arising in the framework of FCA.
The 8th FCA4AI workshop, co-located with ECAI 2020, is (as usual) 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.
The workshop welcomes submissions in pdf format in Springer's LNCS style. Submissions can be technical papers not exceeding 12 pages, or system descriptions or position papers on work in progress not exceeding 6 pages. Submissions are via EasyChair.