Training and application ofneural network language model for ontology population.
P.A. Lomov, M.L. Malozemova
Source record
Source: Crossref
Published: Dec 16, 2020
DOI: 10.37614/2307-5252.2020.8.11.003
Open original source ↗Source abstract
The article considers one of the subtasks of ontology learning -the ontology population, which implies the extension of existing ontology by new instances without changing the ontology structure. A brief overview ofexisting ontology learning approaches and their software implementations is presented. A highly automated technology for ontology population based on training and application of the neural network language model to identify and extract potential instancesof ontology classes from domain texts is proposed. The main stages of its application, as well as the results of its experimental evaluation and the main directions of its further improvement are considered.
Evidence graph
No public relationships recorded yet.
Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.