Accenture Global Solutions Limited

Jiewen Wu

Freddy Lecue

Ian Harris

John Vard

Implementations are directed to receiving current data, processing the current data using a predictive model to provide a result, the result corresponding to a sub-model of the predictive model, determining a set of syntactically similar sub-models based on other data, providing at least one semantic model based on the sub-model of the predictive model, one or more syntactically similar sub-models of the set of syntactically similar sub-models, a domain ontology (knowledge graph), and constraints, the at least one semantic model being provided by merging nodes of the sub-model of the predictive model, and a previously determined sub-model of the predictive model using the domain ontology, a label of the domain ontology being used to label a merged node, determining an interpretation based on the at least one semantic model, the interpretation providing at least one reason for the result, and providing the interpretation.

Interpretation of predictive models using semantic grouping

A device may receive user preference data and company preference data associated with one or more bookable items. The device may obtain external preference data associated with the one or more bookable items. The external preference data may be different from the user preference data and the company preference data. The device may generate a list of schedules based on the user preference data, the company preference data, and the external preference data. The device may generate one or more category scores for a plurality of schedules included in the list of schedules based on the company preference data. The device may rank the list of schedules based on the one or more category scores. The device may select a schedule, from the ranked list of schedules, based on the one or more category scores. The device may perform an action based on selecting the schedule.

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Jiewen Wu