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Towards Scalingless Generation of Formal Contexts from an Ontology in a Triple Store

Authors: Frithjof Dau;

Towards Scalingless Generation of Formal Contexts from an Ontology in a Triple Store

Abstract

The EU-funded research project CUBIST investigates how Formal Concept Analysis can be applied as a Visual Analytics tool on top of information stored in a Triple Store (TS). This paper provides first steps for utilizing SPARQL in order to generate formal contexts out of the data in the TS, where the emphasis is put on using object-properties between individuals. Thus it complements FcaBedrock, which will be used in CUBIST as well and focuses on the scaling of datatype-properties between individuals and literals. It is discussed how the approaches of this paper and FcaBedrock can be combined.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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