Enhancing graph matching techniques with ontologies

Ontologies are being used increasingly in fusion applications, particularly for higher-level fusion, where data must often be understood relationally. This research presents a methodology for utilizing ontologies to enhance the process of graph matching in fusion applications, particularly those associated with soft data (e.g., linguistic data existing in things such as intelligence messages). This paper presents some of the considerations and challenges associated with merging the technologies of ontologies and graph matching, as well as some preliminary research findings that show the effectiveness of using ontologies to enhance the matching capabilities of target graphs (as relational items of interest) against larger data graphs.