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Successfully managing analytics-based semantic relationships and theirprovenance enables determinations of document importance and priority,furthering capabilities for machine-based relevancy scoring operations.Semantic technologies are well suited for modeling explicit and fully qualifiedrelationships but struggle with modeling relationships that are qualified innature, or resultant from applied analytics. Our work seeks to implement theautonomous Directed Qualification of analytic-based relationships by pairingthe Prov-O Ontology (W3C Recommendation) with a relevancy ontology supportinganalytics terminology. This work results in the capability for any semanticallyreferenced document, concept, or named graph to be associated with the resultsof applied analytics as Direct Qualification (DQ) modeled relational nodes.This new capability will enable role, identity, or any other content-basedmeasures of relevancy and analytics-based metrics for semantically describeddocuments.

Enhancing Information Awareness Through Directed Qualification of Semantic Relevancy Scoring Operations