BEGIN:VCALENDAR
VERSION:2.0
TIMEZONE:Europe/Oslo
PRODID:w3-137343@uib.no
URL:https://www.uib.no/nb/node/137343
NAME:Mining EL Bases with Adaptable Role Depth
BEGIN:VEVENT
UID:w3-137343@uib.no
DTSTAMP:20200805T095719Z
DTSTART:20200812T090000Z
DTEND:20200812T100000Z
SUMMARY:Mining EL Bases with Adaptable Role Depth
DESCRIPTION:Description Logic (DL) knowledge bases are one of the most
 prominent ways to formalise and share knowledge without ambiguity.
 They have been particularly successful in fields rich in
 terminological knowledge such as Biology, Medicine, and Manufacturing.
 Although the tools supporting ontology creation and maintenance have
 evolved over the years, building ontologies is still a demanding task.
 In particular, it involves not only ontology engineers, but domain
 experts as well. Moreover, the process of modelling knowledge, even
 with modern methodologies remains time-consuming. In some cases, it is
 possible to build an ontology from a structure (e.g. a database or
 knowledge graph) automatically. By adapting notions from Formal
 Concept Analysis to DLs one extract rules in the form of concept
 inclusions. In DLs, these concept inclusions can involve arbitrarily
 large expressions via nesting. Thus, it is not clear whether a finite
 base exists and, if so, how large concept expressions may need to be.
 We first revisit results in the literature for mining ontologies from
 finite interpretations in the description logic EL. Those mainly focus
 on finding a finite base while fixing the role depth but potentially
 losing some concept inclusions (with larger concepts) that hold in the
 interpretation. Then, we present a new strategy for mining EL bases
 that is adaptable in the sense that it can bound the role depth of
 concepts depending on the local structure of the interpretation
 without losing EL concept inclusions that hold in the interpretation.
LOCATION:Virtual Event
URL:https://www.uib.no/nb/node/137343
CLASS:PUBLIC
TRANSP:TRANSPARENT
END:VEVENT
END:VCALENDAR