Similarity in Semantic Graphs: Combining Structural, Literal, and Ontology-based Measures

Lindsey Vanderlyn, Carl Andersen, Plamen Petrov
2015 Semantic Technologies for Intelligence, Defense, and Security  
Semantic graphs provide a valuable way to represent data while preserving real world meaning. As these graphs become more popular for storing large quantities of data, it is important to have methods of determining similarity between nodes in the graph. This paper extends previous structural similarity algorithms by taking advantage of meaning contained in a graph's literals and the graph's ontology and allowing users to control how much each type of similarity effects overall scores.
more » ... y tests indicate that including these sources of similarity increases scores in way that is better aligned with human intuition.
dblp:conf/stids/VanderlynAP15 fatcat:jwkmcijvszcwzgtt3p4z35tr7q