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Graph-based Ontology Summarization: A Survey
May 15, 2018 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: Graph-based Ontology Summarization: A Survey"
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Authors
Seyedamin Pouriyeh, Mehdi Allahyari, Qingxia Liu, Gong Cheng, Hamid Reza Arabnia, Yuzhong Qu, Krys Kochut
arXiv ID
1805.06051
Category
cs.IR: Information Retrieval
Citations
5
Venue
arXiv.org
Last Checked
3 days ago
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.
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