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On the Combination of Event Calculus and Empirical Semantic Drifts

Authors: Krause, Franz; Yan, Xi; Darnala, Baptiste; Dumontier, Michel;

On the Combination of Event Calculus and Empirical Semantic Drifts

Abstract

The encoding and exploitation of semantics has been gaining popularity, as exemplified by the uptake of digital ontologies and knowledge graphs. However, the semantics of domain objects usually do not reflect how they evolved over time, i.e., which events their dynamic transitions are based on. While a number of methods have been proposed to trace events and their impacts on a domain, there is a paucity of approaches to effectively join them. Thus, we combine event calculus as an analytical approach for modeling causal relationships between events and effects with semantic drifts as an empirical approach for quantifying the impact of domain updates. We demonstrate how their respective weaknesses can be addressed and how their interaction can improve the representation of semantic transitions.

Country
Netherlands
Keywords

Semantic Drift, Dynamic Knowledge Graph, Event Calculus

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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!
0
Average
Average
Average
Green
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