@inproceedings{5cecf0aa869245ab8306cd62dad04c51,
title = "Data-driven diachronic and categorical evaluation of ontologies: Framework, measure, and metrics",
abstract = "Ontologies are a very important technology in the semantic web. They are an approximate representation and formalization of a domain of discourse in a manner that is both machine and human interpretable. Ontology evaluation therefore, concerns itself with measuring the degree to which the ontology approximates the domain. In data-driven ontology evaluation, the correctness of an ontology is measured agains a corpus of documents about the domain. This domain knowledge is dynamic and evolves over several dimensions such as the temporal and categorical. Current research makes an assumption that is contrary to this notion and hence does not account for the existence of bias in ontology evaluation. This work addresses this gap and proposes two metrics as well as a theoretical framework. It also presents a statistical evaluation of the framework and the associated metrics.",
author = "Hlomani Hlomani and Stacey, {Deborah A.}",
note = "Publisher Copyright: Copyright {\textcopyright} 2014 SCITEPRESS - Science and Technology Publications All rights reserved.; 6th International Conference on Knowledge Engineering and Ontology Development, KEOD 2014 ; Conference date: 21-10-2014 Through 24-10-2014",
year = "2014",
doi = "10.5220/0005072700560066",
language = "English",
series = "KEOD 2014 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development",
publisher = "INSTICC Press",
pages = "56--66",
editor = "Joaquim Filipe and Joaquim Filipe and Jan Dietz and David Aveiro",
booktitle = "KEOD 2014 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development",
}