Ontology Summarization: Graph-Based Methods and Beyond

Author:

Pouriyeh Seyedamin1,Allahyari Mehdi2,Liu Qingxia3,Cheng Gong3,Arabnia Hamid Reza4,Atzori Maurizio5,Mohammadi Farid Ghareh4,Kochut Krys4

Affiliation:

1. Department of Information Technology, Kennesaw State University, Marietta, GA 30060, USA

2. Department of Computer Science, Georgia Southern University, Statesboro, GA 30460, USA

3. National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, P. R. China

4. Department of Computer Science, University of Georgia, Athens, GA 30602, USA

5. Department of Mathematics and Computer Science, University of Cagliari, Palazzo delle Scienze, Via Ospedale, 72-09124 Cagliari, Italy

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.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Linguistics and Language,Information Systems,Software

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