RHOG: A Refinement-Operator Library for Directed Labeled Graphs
This work offers a tool for researchers and practitioners working with graph-based data, but it is incremental as it focuses on implementing existing concepts in a library.
The paper introduces the $ρ$G library, which provides foundational operations for directed labeled graphs, including subsumption, refinement, and distance/similarity assessment, with initial support from a National Science Foundation grant.
This document provides the foundations behind the functionality provided by the $ρ$G library (https://github.com/santiontanon/RHOG), focusing on the basic operations the library provides: subsumption, refinement of directed labeled graphs, and distance/similarity assessment between directed labeled graphs. $ρ$G development was initially supported by the National Science Foundation, by the EAGER grant IIS-1551338.