1 citations · 1 across the 2 of their papers we have counts for
6 papers
Explanation Ontology: A Model of Explanations for User-Centered AI
Shruthi Chari, Oshani Seneviratne, Daniel M. Gruen +3
Explainability has been a goal for Artificial Intelligence (AI) systems since their conception, with the need for explainability growing as more complex AI models are increasingly…
Explanation Ontology in Action: A Clinical Use-Case
Shruthi Chari, Oshani Seneviratne, Daniel M. Gruen +3
We addressed the problem of a lack of semantic representation for user-centric explanations and different explanation types in our Explanation Ontology (https://purl.org/heals/eo).…
Directions for Explainable Knowledge-Enabled Systems
Shruthi Chari, Daniel M. Gruen, Oshani Seneviratne +1
Interest in the field of Explainable Artificial Intelligence has been growing for decades and has accelerated recently. As Artificial Intelligence models have become more complex,…
Foundations of Explainable Knowledge-Enabled Systems
Shruthi Chari, Daniel M. Gruen, Oshani Seneviratne +1
Explainability has been an important goal since the early days of Artificial Intelligence. Several approaches for producing explanations have been developed. However, many of these…
Making Study Populations Visible through Knowledge Graphs
Shruthi Chari, Miao Qi, Nkcheniyere N. Agu +5
Treatment recommendations within Clinical Practice Guidelines (CPGs) are largely based on findings from clinical trials and case studies, referred to here as research studies, that…
Linked Open Data Validity -- A Technical Report from ISWS 2018
Tayeb Abderrahmani Ghor, Esha Agrawal, Mehwish Alam +68
Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied by a URI and accessible via HTTP. LOD encodes globalscale knowledge potentially a…