Antonio Zaitoun, Tomer Sagi, & Katja Hose. (2023). OntoEval: an Automated Ontology Evaluation System. In Y. Ding, J. Tang, & J. Sequeda (Eds.), WWW ’23 Companion: Companion Proceedings of the ACM Web Conference 2023 (pp. 82–85). Association for Computing Machinery. https://doi.org/10.1145/3543873.3587318
E192-02 - Forschungsbereich Databases and Artificial Intelligence E192 - Institut für Logic and Computation
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Published in:
WWW '23 Companion: Companion Proceedings of the ACM Web Conference 2023
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ISBN:
9781450394192
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Date (published):
Apr-2023
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Event name:
ACM Web Conference 2023
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Event date:
30-Apr-2023 - 5-May-2023
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Event place:
Austin, Texas, United States of America (the)
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Number of Pages:
4
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Publisher:
Association for Computing Machinery
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Peer reviewed:
Yes
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Keywords:
ontology; natural language processing; BERT; knowledge engineering
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Abstract:
Developing semantically-aware web services requires comprehensive and accurate ontologies. Evaluating an existing ontology or adapting it is a labor-intensive and complex task for which no automated tools exist. Nevertheless, in this paper we propose a tool that aims at making this vision come true, i.e., we present a tool for the automated evaluation of ontologies that allows one to rapidly assess an ontology’s coverage of a domain and identify specific problems in the ontology’s structure. The tool evaluates the domain coverage and correctness of parent-child relations of a given ontology based on domain information derived from a text corpus representing the domain. The tool provides both overall statistics and detailed analysis of sub-graphs of the ontology. In the demo, we show how these features can be used for the iterative improvement of an ontology.
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Project (external):
Israel PBC Independent Research Fund Denmark
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Project ID:
100009443 8048-00051B
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Research Areas:
Logic and Computation: 80% Information Systems Engineering: 20%
