BEGIN:VCALENDAR VERSION:2.0 PRODID:ILLC Website X-WR-TIMEZONE:Europe/Amsterdam BEGIN:VTIMEZONE TZID:Europe/Amsterdam X-LIC-LOCATION:Europe/Amsterdam BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:19700329T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:19701025T030000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:/NewsandEvents/Archives/2020/newsitem/11624/29 -August-2020-8th-Workshop-What-can-FCA-do-for-AI-F CA4AI-2020-Online-via-Zoom DTSTAMP:20200828T000124 SUMMARY:8th Workshop "What can FCA do for AI?" (FC A4AI 2020), Online via Zoom DTSTART;VALUE=DATE:20200829 DTEND;VALUE=DATE:20200829 LOCATION:Online via Zoom DESCRIPTION:Formal Concept Analysis (FCA) is a mat hematically well-founded theory aimed at data anal ysis and classification. FCA allows one to build a concept lattice and a system of dependencies (imp lications and association rules) which can be used for many AI needs, e.g. knowledge processing, kno wledge discovery, knowledge representation and rea soning, ontology engineering as well as informatio n retrieval, recommendation, social network analys is and text processing. Recent years have been wit nessing increased scientific activity around FCA, in particular a strand of work emerged that is aim ed at extending the possibilities of plain FCA w.r .t. knowledge processing. While the capabilities o f FCA are extended, new possibilities are arising in the framework of FCA. The 8th FCA4AI workshop, co-located with ECAI 2020, is (as usual) dedicate d to discuss such issues, and in particular: - Ho w can FCA support AI activities in knowledge disco very, knowledge representation and reasoning, mach ine 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 work shop welcomes submissions in pdf format in Springe r's LNCS style. Submissions can be technical paper s not exceeding 12 pages, or system descriptions o r position papers on work in progress not exceedin g 6 pages. Submissions are via EasyChair. X-ALT-DESC;FMTTYPE=text/html:
Formal Co ncept Analysis (FCA) is a mathematically well-foun ded theory aimed at data analysis and classificati on. FCA allows one to build a concept lattice and a system of dependencies (implications and associa tion rules) which can be used for many AI needs, e .g. knowledge processing, knowledge discovery, kno wledge representation and reasoning, ontology engi neering as well as information retrieval, recommen dation, social network analysis and text processin g. Recent years have been witnessing increased sci entific activity around FCA, in particular a stran d of work emerged that is aimed at extending the p ossibilities of plain FCA w.r.t. knowledge process ing. While the capabilities of FCA are extended, n ew possibilities are arising in the framework of F CA.
\n\nThe 8th FCA4AI workshop, co-locate
d with ECAI 2020, is (as usual) dedicated to discu
ss such issues, and in particular:
\n - How ca
n FCA support AI activities in knowledge discovery
, knowledge representation and reasoning, machine
learning, natural language processing...
\n -
By contrast, how the current developments in AI ca
n 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 v ia EasyChair.