Combining ontology and probabilistic models for the design of bio-based product transformation processes
作者：
Highlights：
• Due to their complexity, reasoning with transformation processes is challenging.
• POND is a workflow aiming to represent and reason with transformation processes.
• Representation is achieved with the ontology PO² and its associated softwares.
• Reasoning under uncertainty is achieved with probabilistic graphical models.
• Expert knowledge integration allows knowledge and causal discovery.
摘要
•Due to their complexity, reasoning with transformation processes is challenging.•POND is a workflow aiming to represent and reason with transformation processes.•Representation is achieved with the ontology PO² and its associated softwares.•Reasoning under uncertainty is achieved with probabilistic graphical models.•Expert knowledge integration allows knowledge and causal discovery.
论文关键词：Ontologies,Probabilistic relational models,Knowledge discovery,Causality
论文评审过程：Received 18 November 2021, Revised 18 January 2022, Accepted 25 April 2022, Available online 7 May 2022, Version of Record 13 May 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.117406
