Abstract
The understanding of results of Knowledge-based systems (KBS) working on complex Dynamic Systems (DS) requires expert knowledge and interpretation capability in order to make a correct analysis of observations at multiple scales and instants. Normally, these kinds of KBS generate extensive inference-trees before showing a definitive result to final users; these inference-trees are not included in the KBS outputs, but they could provide additional information to understand the functioning of the KBS, and also to understand the overall performance of a DS. This document describes a method to generate natural language explanations, based on the results reached by a KBS in respect to a DS behavior, using a specific ontology and discourse patterns. The input of the method is an intermediate-state tree (the inference-tree) and specific domain knowledge represented on domain ontology. The document describes also the software architecture to generate the explanations and the test cases designed to validate the results in a specific domain.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
