Graph-Based Methods for Ontology Summarization: A Survey
Document Type
Conference Proceeding
Publication Date
2018
Publication Title
Proceedings of the IEEE First International Conference on Artificial Intelligence and Knowledge Engineering
DOI
10.1109/AIKE.2018.00020
ISBN
978-1-5386-9555-5
Abstract
Ontologies have been widely used in numerous and varied applications, e.g., to support data modeling, information integration, and knowledge management. With the increasing size of ontologies, ontology understanding, which is playing an important role in different tasks, is becoming more difficult. Consequently, ontology summarization, as a way to distill key information from an ontology and generate an abridged version to facilitate a better understanding, is getting growing attention. In this survey paper, we review existing ontology summarization techniques and focus mainly on graph-based methods, which represent an ontology as a graph and apply centrality-based and other measures to identify the most important elements of an ontology as its summary. After analyzing their strengths and weaknesses, we highlight a few potential directions for future research.
Recommended Citation
Pouriyeh, Seyedamin, Mehdi Allahyari, Qingxia Liu, Gong Cheng, Hamid Reza Arabnia, Maurizio Atzori, Krys Kochut.
2018.
"Graph-Based Methods for Ontology Summarization: A Survey."
Proceedings of the IEEE First International Conference on Artificial Intelligence and Knowledge Engineering: 85-92 Laguna Hills, CA: IEEE.
doi: 10.1109/AIKE.2018.00020 isbn: 978-1-5386-9555-5
https://digitalcommons.georgiasouthern.edu/compsci-facpubs/215
