CG2A: Conceptual Graphs Generation Algorithm
Adam Faci, Marie‐Jeanne Lesot, Claire Laudy · Atlantis studies in uncertainty modelling/Atlantis Studies in Uncertainty Modelling · 2021
Conceptual Graphs (CGs) are a formalism to represent knowledge.The production of CG benchmarks is currently a crucial need in the community to validate algorithms.This paper proposes CG2A, an algorithm to build synthetic CGs exploiting most of their expressivity.CG2A takes as input constraints that constitute ontological knowledge including a vocabulary and a set of CGs with some label variables, called γ-CGs, as components of the generated CGs.Extensions also enable the automatic generation of the set of γ-CGs and vocabulary to ease the database generation and increase variability.