Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 1109–1117 (2017)
Abstract. This article proposes an ontology design pattern leading knowledge providers to represent knowledge in more normalized, precise and inter-related ways, hence in ways that help automatic matching and exploitation of knowledge from different sources. This pattern is also a knowledge sharing best practice that is domain and language independent. It can be used as a criteria for measuring the quality of an ontology. This pattern is: ``using binary relation types directly derived from concept types, especially role types or process types''. The article explains this pattern and relates it to other ones, thereby illustrating ways to organize such patterns. It also provides a top-level ontology for generating relation types from concept types, e.g., those from lexical ontologies such as those derived from the WordNet lexical database. This generation and categorization helps normalizing knowledge, reduces having to introduce new relation types and helps keeping all the types organized.
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