Automated Ontology Evaluation: Evaluating Coverage and Correctness using a Domain Corpus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Ontologies conceptualize domains and are a crucial part of web semantics and information systems. However, re-using an existing ontology for a new task requires a detailed evaluation of the candidate ontology as it may cover only a subset of the domain concepts, contain information that is redundant or misleading, and have inaccurate relations and hierarchies between concepts. Manual evaluation of large and complex ontologies is a tedious task. Thus, a few approaches have been proposed for automated evaluation, ranging from concept coverage to ontology generation from a corpus. Existing approaches, however, are limited by their dependence on external structured knowledge sources, such as a thesaurus, as well as by their inability to evaluate semantic relationships. In this paper, we propose a novel framework to automatically evaluate the domain coverage and semantic correctness of existing ontologies based on domain information derived from text. The approach uses a domain-tuned named-entity-recognition model to extract phrasal concepts. The extracted concepts are then used as a representation of the domain against which we evaluate the candidate ontology's concepts. We further employ a domain-tuned language model to determine the semantic correctness of the candidate ontology's relations. We demonstrate our automated approach on several large ontologies from the oceanographic domain and show its agreement with a manual evaluation by domain experts and its superiority over the state-of-the-art.

Original languageEnglish
Title of host publicationACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023
PublisherAssociation for Computing Machinery, Inc
Pages1127-1137
Number of pages11
ISBN (Electronic)9781450394161
DOIs
StatePublished - 30 Apr 2023
Externally publishedYes
Event2023 World Wide Web Conference, WWW 2023 - Austin, United States
Duration: 30 Apr 20234 May 2023

Publication series

NameCompanion Proceedings of the ACM Web Conference 2023

Conference

Conference2023 World Wide Web Conference, WWW 2023
Country/TerritoryUnited States
CityAustin
Period30/04/234/05/23

Bibliographical note

Publisher Copyright:
© 2023 Owner/Author.

Keywords

  • BERT
  • knowledge engineering
  • natural language processing
  • ontology

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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