Year: 2021
Type: preprint
Abstract: Ontologies comprising of concepts, their attributes, and relationships are used in many knowledge based AI systems. While there have been efforts towards populating domain specific ontologies, we examine the role of document structure in learning ontological relationships between concepts in any document corpus. Inspired by ideas from hypernym discovery and explainability, our method performs about 15 points more accurate than a stand-alone R-GCN model for this task.
Source: arXiv (Cornell University)
Authors: Shalghar, Abhay M, Kumar, Ayush, Ganesan, Balaji, Kannan, Aswin, Parekh, Akshay, G, Shobha
Language: English
Topic: Semantic Web and Ontologies
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3157333265