Formalising contextual expert knowledge for causal discovery in linked knowledge graphs about transformation processes: application to processing of bio-composites for food packaging
by Melanie Munch; Patrice Buche; Hélène Angellier-Coussy; Cristina Manfredotti; Pierre-Henri Wuillemin
International Journal of Metadata, Semantics and Ontologies (IJMSO), Vol. 16, No. 1, 2022

Abstract: With numerous parameters and criteria to take into account, transformation processes are a challenge to model and reason about. This work can be eased thanks to knowledge graphs, which are a widespread practice for formalising knowledge associated with structured and specialised vocabulary about a given domain. They allow to draw semantic relations between concepts, and thus offer numerous tools for reasoning over complex queries. Yet, some of these queries in transformation processes might rely on an additional layer hard to transcribe: uncertainty. In this article, we present how knowledge graphs and probabilistic models can benefit each other for reasoning over transformation processes and address the necessity of formalising contextual expert knowledge for this combination. We then show how this can be used for (1) reverse engineering approaches and (2) linking knowledge bases, through a detailed example on the process of bio-composites for food packaging.

Online publication date: Wed, 31-May-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Metadata, Semantics and Ontologies (IJMSO):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com