Confidentiality
higherabstractionlevelratherthanspecificfeatures.Bydoingso,explanationsavoidexposingsensitivedetails
Privacy
regarding the demand forecasting models, thus preserving confidentiality. In addition, the Knowledge Graph
enableslinkingdomainknowledge,forecastedvalues,andforecastexplanationswhilealsoprovidinginsights
into actionable aspects on which users can take action. The ontology and dataset we developed for this use
case are publicly available for further research.
the semantic closeness of concepts encoded in data features or inte-
grateknowledgegraphembeddingstoaforecastingmodeltoproduce
explanationsalongwiththeforecasts[1,2].
ExplanationofanAImodelshouldprovidecuesonfactorsthatin-
fluencedaforecast,providemeanstodiscernrelevantcontext,support-
ing information, and emphasize actionable aspects to assist decision-
making.Ourresearchfocusesonlocal-levelexplanationssothatplan-
nerscanstillweighcuesprovidedforeachcase.Wedevelopadomain-
Knowledge-graph-based-rich-and-confidentiality-preserving-Ex_2022_Informatio